Up Front - CHI Conferences - Cambridge Healthtech Institute

Cambridge Healthtech Media Group 

www.bio-itworld.com 

Indispensable Technologies Driving Discovery, Development, and Clinical Trials NOVEMBER | DECEMBER 2011 • VOL. 10, NO. 6 

Start Spreading 

the News 

A remarkable coalition 

gives rise to the New York 

Genome Center. 

Page 8 

THE CLOUD COMPUTING 

HORIZON 32 

MEDCO’S X PRIZE MISSION 40 

OPEN SEASON AT 

BIO-IT WORLD EUROPE 11 

Download a PDF 

of This Issue 

SEE PAGE 4 

Nancy Kelley, the 

founding executive 

director of the New 

York Genome Center

19th International 

Moscone North Convention Center 

San Francisco, CA 

February 19-20 

NeW-symposia 

Targeting Cancer Stem Cells 

Cloud Computing 

Display of Difficult Targets 

Point-of-Care Diagnostics 

Next-Generation Pathology 

Molecular Med 

Pharma-Bio Partnering Forums 

February 20 

Event short courses 


Core Programs 

Diagnostics Channel 

Organized by Cambridge Healthtech Institute 


Drug Discovery & Development Channel 

Informatics Channel 

Cancer Channel 

get 

inspired 

Attend. Discover. Apply. 

Spanning five days this year! 

Special Early Bird Registration 

until January 13, 2012 

Save up To $140! 

New This Year! 

TRI-CON All Access PAckAge 

Includes 1 Symposium / Partnering Forum, 

2 Short Courses, and 1 Core Program. 

See website for details. 

TriConference.com

Contents [11–12•11] 

Feature Story 

The Utility of Cloud Computing 

How cloud computing is being used today— 

and tomorrow—in life sciences. 32 

Up Front 

8 A Genome Center for Gotham City 

11 Open Data and Patient Modeling in Europe 

14 New Technologies for Patient-Physician 

Interaction at Medicine 2.0 

Bush Doctrine 

15 Clouds for GLP Environments? 

Skeptical Outsider 

16 Science in Thrall to the FDA 

Insights | Outlook 

17 NGS by the Numbers 

12 Briefs 

Clinical Trials 

21 An Inside Perspective on PAREXEL 

24 Survey Says Tool Up for Smarter Studies 

26 NuMedii’s ‘De-Risks’ Drug Repositioning Work 

Computational Biology 

27 PerkinElmer Targets Holistic Data Solutions 

30 What’s in a Name: Systems Biology 

[4] BIO•IT WORLD NOVEMBER | DECEMBER 2011 www.bio-itworld.com 

Next-Gen Data 

40 New Rules for Archon Genomics X Prize 

41 DNAnexus to Mirror SRA Database 

in Google Cloud 

42 Inova/Complete Deal for ‘Next-Gen Medicine’ 

43 Genia’s Nanopore/Microchip Technology Gains 

Life Technologies’ Support 

IT/Workflow 

45 Sophia Technology: Making Semantic Sense of 

Unstructured Data 

48 BT Connecting People and Patients 

In Every Issue 

First Base BY KEVIN DAVIES 

5 Dr. Watson, I Presume? 

The Russell Transcript BY JOHN RUSSELL 

54 Crescendo Bioscience’s Aspirations 

6 Company & Advertiser Index 

50 New: Free Trials & Downloads 

51 New Products 

52 Educational Opportunities 


of This Issue 

CLICK HERE! 

8 24 32 

Cover photo by Katja Heinemann

First Base 

Dr. Watson, 

I Presume? 

KEVIN DAVIES 

Normally in October, I travel with colleagues to Germany 

to participate in the annual Bio-IT World 

Europe conference (see p. 11). This year, I felt obliged 

to beg off. The International Congress of Human 

Genetics had called to ask if I’d be interested in moderating 

a plenary panel discussion to open the 2011 

conference. The title was “Whole Genome Sequencing: To do it 

or not to do it?” and the guest of honor 

was James D. Watson, Nobel laureate. 

It wasn’t much of a decision. 

We last featured the doyen of DNA 

in this magazine in 2003, on the occasion 

of the 50 th anniversary of the publication 

of the double helix paper in 

Nature (see “Genes, Girls, and Honest 

Jim,” Bio•IT World April 2003). Watson 

gave a press conference in Miami, 

where he reflected on that iconic 

achievement, even suggesting that if 

the BBC were ever to remake the film 

of that discovery, he’d like to be played 

by Ben Stiller (more recently, he suggested 

Sacha Baron Cohen). 

Made in Manhattan 

We seldom, if ever, feature a non-scientist on the 

cover of Bio•IT World, but this issue proves a worthy 

exception. As revealed in her first major interview, 

Nancy Kelley and friends have pulled off something 

remarkable—the creation of the New York Genome 

Center (see p. 8), supported and funded by a remarkable 

coalition of academic institutions, corporate 

partners and private philanthropists. 

If this was easy, somebody would have figured 

out a way to pull this off a long time ago. It speaks 

volumes of Kelley’s administrative skills and determination 

that, as the founding executive director of 

the Center, she was able to engineer such a feat. The 

irony is that it took a Bostonian to bring a worldclass 

genomics center to the heart of New York. 

IPI PHOTO, MONTREAL 

L to R: James D. Watson (Cold Spring Harbor Laboratory), 

Kevin Davies, and Marjolein Kriek (University 

of Leiden, The Netherlands). 

Now 83, Watson is the Chancellor Emeritus of the Cold 

Spring Harbor Laboratory on Long Island. He was also the 

first person sequenced using a next-generation sequencing 

platform, in 2007. As Jonathan Rothberg, the founder of 454 

Life Sciences, the company that sequenced Watson’s DNA, remarked, 

“You’re the first genome for the rest of us.” 

Watson spoke candidly about his personal genome sequence. 

What had he learned from his sequence? Not much, 

it turns out. A slight adjustment to his beta blockers. From the 

outset, he asked not to be told about his APOE status, which 

could reveal an increased risk for Alzheimer’s disease, and discussed 

the latest theory about the neighboring gene that might 

have a physiological role in the disease. 

Any audience with “Honest Jim” is likely to be colorful, and 

this was no exception. He elicited cheers when he besmirched 

a well-known biotech company defending a controversial 

gene patent, spoke movingly about his son’s diagnosis with 

schizophrenia, while making others uncomfortable (or worse) 

in talking (albeit compassionately) about “genetic losers.” 

Once the discussion was over, he was 

mobbed by photograph and autograph 

seekers clutching their wellworn 

copies of The Double Helix. 

The other panelists—Jim Lupski 

(Baylor), Seong-Jin Kim (CHA University, 

Korea), and Marjolein Kriek 

(Leiden, The Netherlands)—are all 

genome pioneers in their own right, 

and contributed to a fascinating 

discussion. 

The Digital World 

Watch the video of James D. 

Watson and fellow panelists 

from ICHG 2011. 

After nearly 10 years of printing a hard copy of 

Bio•IT World magazine, this issue will become something 

of a collector’s item. Starting in January 2012, 

we will publish exclusively as a digital magazine. 

We’ve weighed the costs of printing and mailing 

many thousands of issues versus our keen desire to expand the frequency 

and global reach of Bio•IT World. 

Earlier this year, we launched a free 

iPad app for Bio•IT World that not only 

shows off the printed content but also 

features video and other enhancements 

that will only grow in 2012. If you haven’t 

checked out or taken out a free subscription 

to our digital content, simply go to: 

http://bit.ly/bioitnew 

www.bio-itworld.com NOVEMBER | DECEMBER 2011 BIO•IT WORLD [ 5 ] 

CONTENTS

CONTENTS 

Company Index 

454 Life Sciences . . . . . . . . . . . . 5 

Accenture . . . . . . . . . . . . . . . . . 48 

Active Motif . . . . . . . . . . . . . . . . 51 

Affymetrix . . . . . . . . . . . . . . . . . 43 

Amazon . . . . . . . . . . . . . . .11, 33 

Amylin Pharmaceuticals . . .33, 37 

APEX International . . . . . . . . . . . 22 

Appistry . . . . . . . . . . . . . . . . . . 38 

Applied Biosystems . . . . . . . . . . 48 

Archon Genomics X Prize . . . . . . 40 

Argonne National Laboratory . . . 11 

Aspera . . . . . . . . . . . . . . . . . . . 37 

Assay Depot . . . . . . . . . . . . . . . 37 

Baylor . . . . . . . . . . . . . . . . . . . . . 5 

BGI . . . . . . . . . . . . . . . .12, 29, 42 

BIOBASE . . . . . . . . . . . . . . . . . . 50 

BioTeam . . . . . . . . . . . . . . .36, 49 

Brainloop . . . . . . . . . . . . . . . . . 50 

BT Global Services . . . . . . . . . . 48 

CambridgeSoft . . . . . . . . . . . . . 27 

Celera Genomics . . . . . . . . . . . . 48 

Center for Computational and 

Systems Biology Center . . . . . 11 

CHA University . . . . . . . . . . . . . . 5 

ChemAxon . . . . . . . . . . . . .38, 50 

CLC bio . . . . . . . . . . . . . . . . . . . 50 

ClearTrial . . . . . . . . . . . . . . . . . . 24 

Cold Spring Harbor Laboratory . . 5 

Complete Genomics . . . . . .38, 42 

Crescendo Bioscience . . . . . . . . 54 

Cycle Computing . . . . . . . . . . . . 36 

Definiens . . . . . . . . . . . . . . . . . 51 

Dell . . . . . . . . . . . . . . . . . . . . . . 48 

DNAnexus . . . . . . . . . . . . . .36, 41 

Eagle Genomics . . . . . . . . .33, 49 

Enlis Genomic . . . . . . . . . . . . . . 50 

Advertiser Index 

VOLUME 10, NO. 6 

Entelos . . . . . . . . . . . . . . . . . . . 54 

Eucalyptus . . . . . . . . . . . . . . . . 33 

European Bioinformatics 

Institute . . . . . . . . . . . . . . . . . 11 

Food and Drug Administration . . 16 

Gartner . . . . . . . . . . . . . . . . . . . 24 

Genentech . . . . . . . . . . . . . . . . 36 

Genia . . . . . . . . . . . . . . . . . . . . 43 

GenoLogics . . . . . . . . . . . . . . . . 12 

Geospiza . . . . . . . . . . . . . . . . . . 27 

GlaxoSmithKline . . . . . . . . . . . . 38 

goBalto . . . . . . . . . . . . . . . . . . . 50 

GoGrid . . . . . . . . . . . . . . . . . . . 33 

Google . . . . . . . . . . . . .33, 36, 41 

GSK . . . . . . . . . . . . . . . . . . . . . 26 

Harvard Medical School . . .34, 36 

HealthTap . . . . . . . . . . . . . . . . . 14 

Helicos . . . . . . . . . . . . . . . . . . . 17 

HP . . . . . . . . . . . . . . . . . . . . . . 48 

IBM . . . . . . . . . . . . . . . . . . .11, 48 

Illumina . . . . . . . . .12, 17, 29, 51 

Ingenuity Systems . . . . . . . . . . . 54 

Inova Translational Medicine 

Institute . . . . . . . . . . . . . . . . . 42 

Institute for Systems Biology . . . 30 

Intel . . . . . . . . . . . . . . . . . . . . . 11 

IO Informatics . . . . . . . . . . . . . . 51 

Ion Torrent . . . . . . . . . . . . . . . . . 17 

Johnson & Johnson . . . . . . . . . . 33 

Karlsruhe Institute of 

Technology . . . . . . . . . . . . . . . 11 

Max Planck Institute for 

Molecular Genetics . . . . . . . . 11 

Max Planck Institute of Molecular 

Cell Biology and Genetics . . . 11 

Medco Health Solutions . . . . . . 40 


Myriad Genetics . . . . . . . . . . . . 54 

NABsys . . . . . . . . . . . . . . . . . . . 44 

NCBI . . . . . . . . . . . . . . . . . . . . . 41 

New York Genome Center . . . . . , 5 

NimbleGen . . . . . . . . . . . . . . . . 28 

Nimbus . . . . . . . . . . . . . . . . . . . 33 

Nirvanix Cloud . . . . . . . . . . . . . . 37 

NobleGen . . . . . . . . . . . . . . . . . 44 

Novartis . . . . . . . . . . . . . . . . . . 26 

NuMedii . . . . . . . . . . . . . . . . . . 26 

Omixon . . . . . . . . . . . . . . . . . . . 50 

Opscode . . . . . . . . . . . . . . . . . . 37 

Oracle . . . . . . . . . . . . . . . . . . . . 51 

Oxford Nanopore . . . . . . . . . . . . 44 

Pacific Biosciences . . . .17, 36, 43 

Penguin . . . . . . . . . . . . . . . . . . . 33 

PerkinElmer . . . . . . . . . . . . . . . . 27 

Pfizer . . . . . . . . . . . . . . . . . . . . . 26 

Praxeon . . . . . . . . . . . . . . . . . . . 50 

Rackspace . . . . . . . . . . . . . . . . 33 

Real Time Genomics . . . . . . . . . 50 

Roche . . . . . . . . . . . . . . . . . . . . 28 

San Diego Supercomputer 

Center . . . . . . . . . . . . . . . . . . 38 

Schrodinger . . . . . . . . . . . . . . . . 49 

Siemens . . . . . . . . . . . . . . . . . . 11 

Stanford University . . . . . . .14, 26 

SYM-BIO Life Sciences . . . . . . . 28 

Univa UD . . . . . . . . . . . . . . . . . 36 

University of California 

Davis . . . . . . . . . . . . . . . . . . . 12 

University of California 

Santa Cruz . . . . . . . . . . . . . . . 43 

University of Chicago . . . . . . . . . 11 

University of Leiden . . . . . . . . . . . 5 

University of Manchester . . .12, 12 

Advertiser Page # Advertiser Page # 

Appistry....................................... 31 

www .Appistry .com 

Barnett Educational Services: PAREXEL Biopharmaceutical 

R&D Statistical Sourcebook 2011/2012.......... 47 

www .barnettinternational .com 

Bio-IT World Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 

Bio-ITWorldAsia .com 

Bio-IT World Best Practices Awards .................. 35 

Bio-ITWorld .com/bp_awards .aspx 

Bio-IT World Conference & Expo ..................18-19 

Bio-ITWorldExpo .com 

BioPartnering North America....................... 55 

Techvision .com/bpn 

Dell Compellent.................................. 7 

Inetpresent .com/w/Dell/136/reg/ 

Educational Opportunities.......................52-53 

Bio-ITWorld .com 

Life Sciences Innovation Forum..................... 56 

www .LSInnovation .com 

Molecular Med TRI-CON 2012....................... 2 

TriConference .com 

Panasas........................................ 3 

Panasas .com 

RSA Conference ................................ 23 

RSAConference .com/bioit 

SciEngines..................................... 20 

www .sciengines .com 

SGI ......................................... 13 

www .sgi .com/go/bio-it 

This index is provided as an additional service. The publisher does not assume any liability for errors or omissions. 

Editorial, Advertising, and Business Offices: 250 First Avenue, Suite 300, Needham, MA 02494; (781) 972-5400 

Bio•IT World (ISSN 1538-5728) is published bi-monthly by Cambridge Bio Collaborative, 250 First Avenue, Suite 300, Needham, MA 02494 . 

Bio •IT World is free to qualified life science professionals . Periodicals postage paid at Boston, MA, and at additional post offices . The one-year 

subscription rate is $199 in the U .S ., $240 in Canada, and $320 in all other countries (payable in U .S . funds on a U .S . bank only) . 

Subscriptions: Address inquires to Bio-IT World, 250 First Avenue, Suite 300, Needham, MA 02494 888-999-6288 or e-mail 

kfinnell@healthtech .com 

Reprints: Copyright © 2011 by Bio-IT World All rights reserved . Reproduction of material printed in Bio •IT World is forbidden without written 

permission . For reprints and/or copyright permission, please contact Tim McLucas, (781) 972-1342, tmclucas@healthtech .com . 

Indispensable Technologies Driving 

Discovery, Development, and Clinical Trials 

EDITOR-IN-CHIEF 

Kevin Davies (781) 972-1341 

kevin_davies@bio-itworld .com 

MANAGING EDITOR 

Allison Proffitt (617) 233-8280 

aproffitt@healthtech .com 

ART DIRECTOR 

Mark Gabrenya (781) 972-1349 

mark_gabrenya@bio-itworld .com 

VP BUSINESS DEVELOPMENT 

Angela Parsons (781) 972-5467 

aparsons@healthtech .com 

VP SALES — 

LEAD GENERATION PROGRAMS 

Alan El Faye (213) 300-3886 

alan_elfaye@bio-itworld .com 

ACCOUNT MANAGER 

Tim McLucas (781) 972-1342 

tmclucas@healthtech .com 

CORPORATE MARKETING 

COMMUNICATIONS DIRECTOR 

Lisa Scimemi (781) 972-5446 

lscimemi@healthtech .com 

WEB ADVERTISING OPERATIONS MANAGER 

Franscena Schandelmayer-Davis 

(781) 972-1351 

fsdavis@healthtech .com 

ADVERTISING OPERATIONS COORDINATOR 

Stephanie Cline (781) 972-5465 

scline@healthtech .com 

Contributing Editors 

Michael Goldman, Karen Hopkin, 

Deborah Janssen, John Russell, 

Salvatore Salamone, Deborah Borfitz 

Ann Neuer, Tracy Smith Schmidt 

Advisory Board 

Jeffrey Augen, Mark Boguski, 

Steve Dickman, Kenneth Getz, 

Jim Golden, Andrew Hopkins, 

Caroline Kovac, Mark Murcko, 

John Reynders, Bernard P. Wess Jr. 

Cambridge Healthtech Institute 

PRESIDENT 

Phillips Kuhl 

Contact Information 

editor@healthtech.com 

250 First Avenue, Suite 300 

Needham, MA 02494 

Follow us on Twitter, LinkedIn, and Facebook 

http://twitter .com/bioitworld 

www .linkedin .com/groupRegistration?gid=3141702 

www .facebook .com/bioitworld 

®

COMPLIMENTARY LIVE WEBINAR: 

Meeting Compliance Needs through 

Enhanced Management of Patient Data 

Date: December 8, 2011 

Time: 1PM/EST 

Length: 60 minutes 

Sponsored by 

Description: Healthcare providers understand the pressure to keep the 

data center highly-available at all times. These organizations consistently 

try to manage rapidly growing digital patient data, while adhering to 

regulatory compliance that dictates how long it must be stored. Learn 

how Radiology Ltd. has utilized the Dell Compellent SAN to improve 

the performance and scalability of its data center, while gaining critical 

transparent reporting to help enable better patient care. 

Presenter: Colin Schmugge/Data Center Manager at Radiology, Ltd. 

Moderator: Dr. Kevin Davies, Editor-in-Chief, Bio-IT World 

Colin Schmugge started with Radiology Ltd in 1996 as an x-ray darkroom 

technician. He then worked as a computer technician from 2004-2006 

before moving on to become the help desk manager. He continued to 

work his way through various IT management roles—each with increasing 

responsibilities--before taking on the data center manager position in 

2009. Colin holds a bachelor’s degree in engineering management from 

the University of Arizona. 

Register today: www.inetpresent.com/w/Dell/136/reg/

CONTENTS 

Up Front News 

A Genome Center for Gotham City 

Nancy Kelley nurtures the New York Genome Center. 

It is fair to say that Nancy Kelley, the executive director of the New York Genome Center 

(NYGC), did not expect to be leading such an ambitious effort 12 months ago. But 

convinced of the potential to create a major genomics institute in the center of New 

York city, Kelley relentlessly lobbied, marshaled and cajoled a consortium of all the 

major New York institutes and medical centers, along with private philanthropists 

and corporate partners, that it was time to seize the day. 

Kelley’s name may not be widely known in scientific circles because, as she freely 

admits, she’s not a scientist. But this economist, lawyer, and commercial real estate 

developer has been working in science for more than over 25 years, landing on the 

Board of the Jackson Laboratory and helping numerous biotech companies grow their 

business through stints at Spaulding & Slye Colliers and Alexandria Real Estate. Two 

years ago, she began working with a client building a personalized medicine institute. 

Those discussions took her to New York, where Kelley, aided by Columbia University 

molecular biologist Tom Maniatis and others, began fleshing out plans for NYGC. 

For the past year, Kelley has been working as NYGC’s executive director, helping to 

raise some $120 million in advance of the center’s official opening in Manhattan in 

early 2012. 

Prior to the formal announcement of NYGC on November 3 in Manhattan, Kelley 

gave her first in-depth interview with Bio•IT World editor Kevin Davies and talked 

about the extraordinary effort to bring a world-class genome center to the Big Apple, 

and what it means for the New York scientific and medical establishment. 

(Remarks have been edited for brevity. The full interview can be found at: 

www.bio-itworld.com/news/11/2011/new-york-genome-center.html) 

Bio•IT World: Nancy, how has your 

diverse background led you to your 

current role as executive director? 

Kelley: I’ve worked in the private sector, 

non-profit and public sector at various senior 

levels throughout my career. I started 

as a young lawyer at Hale & Dorr as a 

corporate securities lawyer, representing 

start-up companies. My standard client 

was a doctor or scientist who walked out 

of MIT or Harvard and we’d help build 

a company around it. I had the good 

fortune of seeing a lot of life science and 

health care companies develop from infancy, 

we’d help negotiate IP, raise money, 

put the management teams together, financing 

etc. If they were successful they’d 

grow up to go public and develop their 

drug…. It not only gave me a really nice 

education about how organizations grow 

and develop over time, but it helped me to 

understand the science. It was my job as 

the lawyer to sit down with the scientists 

and write down what they were doing in 

English for investors, so people buying 

their securities would actually under- 


stand what they were doing! 

It was also a wonderful chance to 

work with some big companies that were 

babies back then, like Genetics Institute. 

Eventually, I found myself working with 

start-ups to raise money and to help run 

them, whether for profit or non-profit... 

In the last ten years, I became involved 

in life science real estate development. 

I helped negotiate a major transaction 

on behalf of my hometown—Belmont, 

Mass—with McLean Hospital… It turned 

out that life science real estate is a technologically 

very sophisticated product that 

has to be marketed and developed in a way 

completely different than other real estate. 

I thought it was an intriguing challenge. 

Tell us about the origins of the New York 

Genome Center. 

I’d been working in the city for nearly ten 

years in life sciences with Spaulding & 

Slye Colliers as well as Alexandria Real 

Estate. As senior VP of strategic operations 

for Alexandria, I was responsible for 

responding for the New York City RFP 

KATJA HEINEMANN 

and creating the development of the East 

River Science Park, which is 1 million 

square feet in Manhattan… Manhattan 

isn’t an easy place to develop anything in. 

It was a very large project—three towers, 

nearly $1 billion and 1 million square feet. 

The combination of legal, financial, 

operational and real estate with the scientific 

background all came together to 

create an opportunity in New York. I’d 

been an independent consultant for two 

years after Alexandria. I’d been working 

on another large sequencing project for a 

client for almost 12 months, which didn’t 

materialize. But it opened up the idea 

and possibility of introducing the idea of 

a large sequencing operation in New York. 

Given the fact I’d been working there for 

ten years and had many long-standing 

relationships with scientists there, I 

brought it to New York to see if there was 

interest. So we started discussing it and 

things developed from there. 

Obviously there was… a lot of skepticism 

about this, and it’s continued right 

through until today. But as I say, the only 

thing you can do is try. After consulting 

with a few individual scientists, we pulled 

together a very large meeting with representatives 

from all the institutions [in 

August 2010], and asked them to participate 

in the creation of a center like this. It

started with Columbia, went to Sloan Kettering 

and Rockefeller University… They 

enthusiastically endorsed it, to the extent 

that within 30 days, we had eight institutions 

putting seed money into a feasibility 

study and agreeing to move forward… 

THE MISSION 

How would you describe the vision, 

the mission of NYGC? 

The vision for NYGC is really to achieve 

transformational results for health care 

and research. In the end, our success will 

be measured by how the center affects 

medical delivery the way research is being 

done. For New York in particular, this is 

a very exciting development. For a long 

time, they’ve had the leading global institutions 

in health care, but for whatever 

reason, haven’t always come together to 

collaborate and leverage that strength. 

With this enterprise, it will allow them to 

do that and take their role on the global 

stage, as they should be… 

It will involve a very large highthroughput 

sequencing center, offering 

services not only to founding members 

but to other institutions and companies. 

It will also have a very strong research 

element, driving it forward with both 

genomics and bioinformatics involved. 

Who else has played a key role in 

organizing NYGC? 

The first and probably most important is 

Tom Maniatis at Columbia, a renowned 

and accomplished scientist, someone I’ve 

known from the Jackson Lab. He’s also a 

serial entrepreneur, having built some of 

the best known companies in the life sciences 

field, including Genetics Institute. 

He was the first person whom I talked 

to about this, and has been instrumental 

at every level in guiding this forward. So 

we’ve really done this together. 

But I’d also point to other key individuals—Tom 

Kelly (Sloan Kettering) has 

been involved from the beginning. New 

leaders at Sloan Kettering and Rockefeller, 

Craig Thompson and Marc Tessier- 

Lavigne respectively, were recruited and 

understood the need for inter-institutional 

and private sector collaboration. Russ 

Carson (founder/chair, Welsh Carson and 

the New York City Investment Fund) immediately 

saw the benefits of this to the 

New York Genome Center 

Charter Members 

Institutional Founding Members: 

Cold Spring Harbor Laboratory 

Columbia University 

Cornell University/Weill Cornell Medical 

College 

The Jackson Laboratory 

Memorial Sloan-Kettering Cancer 

Center 

Mount Sinai School of Medicine 

New York-Presbyterian Hospital 

New York University/NYU School of 

Medicine 

North Shore-Long Island Jewish Health 

System 

The Rockefeller University 

Stony Brook University 

Associate Founding Member: 

Hospital for Special Surgery 

Additional Members/Collaborators: 

F. Hoffmann-La Roche 

Illumina 

Support from: 

Empire State Development Corp. 

New York City Economic Development 

Corp. 

New York City Investment Fund 

Philanthropic Donors: 

The Simons Foundation (Founding 

Partner) 

Bloomberg Philanthropies 

Russell L. Carson 

Anthony B. Evnin 

WilmerHale 

city. He is now the Chairman of NYGC’s 

Board of Directors. Tony Evnin (senior 

partner, VenRock) also saw the immediate 

benefit to New York; he was our first 

individual philanthropic donor and has 

also played a critical role. Many, many 

people throughout the New York community 

have been instrumental. 

Why did you choose Illumina as NYGC’s 

sequencing partner? 

We went through a very extensive technology 

selection process, which involved 

all the scientists on the scientific advisory 

committee, and the technology and bioinformatics 

working group committees. We 

invited the two leading companies—Illumina 

and Life Technologies—to come in 

and make a presentation by their senior 

management, how they would approach a 

partnership with a large sequencing cen- 

ter like this... In the end, there’s just been 

enormous progress made by Illumina in 

their productivity and turnaround times 

this year, and that proved to be one of the 

deciding factors—the continuing evolution 

of their technology and widespread 

adoption. 

We will start with approximately 30 

sequencers in year one and build up to 

a fairly significant number over a 5-year 

period. There are many terms to the 

Illumina collaboration, and obviously 

pricing is one of them. But this will not 

be an exclusive technology in any way. In 

the innovation center, we’ll be testing new 

technologies and making them available 

to the scientists in New York. 

BUILDING THE COALITION 

How have you managed to keep all these 

New York institutions happy during 

negotiations? 

The center was legally incorporated and 

raised its initial seed financing in August 

2010. The original feasibility study was 

completed last December and underwent 

extensive review by all the institutions 

in January 2011. We started a planning 

process—meaning implementation— 

which concluded at the end of June. In 

the weeks that followed, we finalized the 

governance and closing documents for 9 

Institutional Founding Members, now 11, 

and transitioned to our build-out process. 

We now are opening a small development 

office, expanding our launch team, and 

negotiating the other agreements that 

will serve as the foundation for our official 

opening in 2012. 

Getting to this point has been very, 

very challenging! A few things helped a 

great deal: first, the commitment from 

the leadership of the various institutions 

to actually sit down and discuss this, 

knowing how important this was going 

to be for New York in general. New York 

is behind in the genomics area, so these 

leaders saw NYGC as a real opportunity to 

catch up. Their commitment to the process 

was very important and helped overcome 

some bumps when we met them. 

What were some of the concerns and 

hesitations you heard regarding NYGC? 

I think there were three substantive 

issues. First, would the institutional de- 


CONTENTS

CONTENTS 


mand be sufficient to sustain a center of 

this magnitude and what would be the 

commitment for those institutions to the 

center and the commitment of the center 

to them? 

Traditionally, New York has lagged 

behind other areas in sequencing capacity, 

as have all the institutions we’ve been 

speaking to—although one or two, like 

Mount Sinai, have been building a large 

genomics capability in recent years. So 

that was a big contentious question that 

continued through the end. Obviously 

with a start-up, nothing is certain and 

everyone has a different idea. We had to 

do as much research as we could and go 

with our gut. We’ll have to adjust as we go 

along, obviously. 

A second major issue was, how would 

the major institutions participate together? 

Would there be equal representation 

or proportional participation with different 

sizes of institutions? In the end, after 

enormous debate, a principle of equal 

representation was chosen. The initial 

contribution by all the founding members 

is the same, even though their use of the 

center may vary dramatically. The idea 

that won out was that the value of participation 

in a scientific community and 

endeavor created by NYGC was worth the 

small initial investment and that everyone 

would share in this scientific enterprise 

equally. 

The third issue was, how would this 

initiative interact with the initiatives 

going on within each of the institutions? 

Competitive or supportive? How would 

that work? This was especially important 

in defining the research element of the 

center, because there is a plan and process 

underway to recruit a world renowned 

scientist to be the scientific director. 

There are a lot of questions about how the 

research portion would interface with the 

other institutions. 

At one point, Richard Gibbs (Director, 

BCM genome center) said something to 

me: ‘You have to be absolutely fearless 

to do this.’ He’s right—if one stopped to 

think too much about all the things that 

could go wrong at any moment, you’d 

never get up in the morning. So the only 

thing you can do is to work at it the best 

you can, manage the issues as they come 

up. I don’t think there was one day this 


year when I had full confidence we’d actually 

make it, but I knew it was important 

to try. 

FUNDING AND LOGISTICS 

What is it costing to get NYGC off the 

ground? 

The total project cost is about $120 

million. It will come from a variety of 

sources—the Institutional Founding 

Members, Associate Members, private 

philanthropists, founding member companies, 

technology collaborators, the New 

York City Economic Development Corporation 

and the New York City Investment 

Fund, That’s not all inclusive, but there 

are a number of pieces to the quilt that 

had to be knit together to be able to put 

this all together. 

What is NYGC’s operating structure? 

We’ve built up the business model with 

seven operational units. We start with 

the sequencing service center, which will 

serve not only the institutional founding 

members and pharma collaborators, but 

also hospitals on the clinical side… That 

will be coupled with a very robust bioinformatics 

presence. 

We’re looking to recruit Ph.D.s— 

mathematicians, and computational biologists, 

to interpret the sequencing data 

and to assist researchers on a consulting 

basis. 

Third, the center will have its own 

internal research, led by a world-class scientific 

director. We’ll also make another 

senior investigator appointment in the 

first year. 

The Innovation Center is a cost center 

where we’re investing a lot of capital and 

operational resources to allow scientists 

from throughout New York and beyond 

to use these instruments, to publish 

early and establish thought leadership. 

Finally, we hope there will be commercial 

activities from these efforts to create new 

jobs and products to enhance medical 

treatments. 

Training will take place in conjunction 

with Cold Spring Harbor’s wonderful programs, 

and possibly with Stony Brook and 

CUNY, with whom we’ve talked about 

creating some degree programs to help 

train people in this area. And finally, we’ll 

have a small philanthropic unit. 

To start, we’ll have two research 

groups with about 15 people each, so 

the internal research will have about 30 

people. 

What about a clinical component? 

Is that a revolution that NYGC aims 

to be a part of? 

Absolutely! There will be a CLIA-certified 

portion of the facility and we’ll be interacting 

very closely with the hospitals 

like NewYork-Presbyterian Hospital and 

North Shore-LIJ, two of our institutional 

founding members, to create some innovative 

programs. Obviously there are a lot 

of regulatory and other issues that need to 

be overcome, but we do think the clinical 

component of this endeavor will be part 

of the future of medicine and health care. 

When do you expect to recruit the 

scientific director, and what will your 

role be after that? 

An international search effort is underway, 

led by a committee comprised of 

representatives of all the institutional 

founding members and myself, chaired 

by Tony Evnin. Obviously, this leadership 

group has a lot of established relationships 

in the industry, so we’re also seeking 

recommendations as to people who 

should be considered. I think it will take 

[several] months to recruit someone who 

has the right scientific, leadership and 

administrative attributes. 

Obviously there’s an enormous 

amount of work to be done to make this 

successful. The first step in creating the 

strategic plan and raising the money is 

only a small component of making this 

successful. There’s a huge ongoing financial, 

executive and operational role that 

has to be put together with a large organization, 

and I’d expect to play a key role 

in doing that as the Executive Director or 

Deputy Director. 

You have to be both proud and relieved 

to have come this far. 

In truth, when I first talked to Tom Maniatis 

and Tom Kelly about this, we were 

operating with a cell phone and a hotmail 

account! 12 months later, to have raised 

$120 million and brought this number 

of institutions together is really quite 

extraordinary. •

Open Data and Patient Modeling in Europe 

Open source debates abounded at 3rd annual Bio-IT World Europe conference. 

BY ALLISON PROFFITT 

HANNOVER, GERMANY—“The tools 

and library situation in bioinformatics is 

an open-source zoo,” said Misha Kapushesksy, 

functional genomics team leader 

with the European Bioinformatics 

Institute (EBI), during his presentation 

on the Gene Expression Atlas platform. 

If that’s so, attendees got quite a tour of 

menagerie at the third annual Bio-IT 

World Europe conference*, with much 

emphasis on open-source platforms and 

cloud deployments. 

The ArrayExpress Archive is an EBI 

database of functional genomics experiments 

where one can query and download 

data. Gene Expression Atlas contains 

a subset of curated and re-annotated 

archive data, which can be queried for 

individual gene expression results under 

different biological conditions across 

experiments. It’s meant to be a simple interface 

for identifying strong differential 

expression candidate genes in conditions 

of interest. 

Kapushesksy and colleagues have deployed 

the ArrayExpress high-throughput 

sequencing pipeline inside the R Cloud at 

EBI. The R Cloud was originally a server 

farm and is EBI’s “experiment to increase 

the use of its infrastructure,” Kapushesksy 

said. The cloud is free, but use is constrained. 

Currently R Cloud is linked to 

the European Nucleotide Archive (ENA), 

ArrayExpress, and quality control reports. 

Daniel White (Max Planck Institute 

of Molecular Cell Biology and Genetics) 

presented Fiji, an extension of the 

ImageJ open platform for image analysis 

but with Java, Java 3D, and plugins organized 

in a menu structure. White said 

that Fiji now represents a philosophy 

and community as well as a platform, 

with users sharing code and developing 

plugins for image transformation, registration, 

segmentation and analysis. 

Urban Liebel (Karlsruhe Institute 

* Bio-IT World Europe 2011, Hannover, Germany, October 

11-13, 2011 

of Technology, KIT) presented the 

Harvester bioinformatics search portal 

(harvester.kit.edu). The portal scours all 

of the images and figures in PubMed and 

more than 30 other databases for images 

of interest. “I don’t know about you,” Liebel 

said, “but when I find a paper, I look 

at the figures first. If I can understand the 

figures, I read the paper.” 

Liebel also presented Sciety (sciety. 

org), an application that works like 

Digg for PubMed articles. Much of the 

post-publishing commentary on papers 

SAVE THE DATES: 

Bio-IT WORLD EUROPE 2012 

New Location: VIENNA, AUSTRIA 

October 9-11, 2012 

isn’t recorded, Liebel said. If a student 

brings a Nature paper to his/her supervisor, 

the group leader may know that the 

paper had been later invalidated, but the 

student doesn’t. Sciety lets researchers 

comment on published research. There 

is an option to comment anonymously, 

but comments from users who log in and 

identify themselves carry more weight. 

Programming the Patient 

Hans Lehrach, director of vertebrate genomics 

at the Max Planck Institute for 

Molecular Genetics in Berlin, presented 

“Systems Patientomics” in one of two 

keynote talks. We’ve been treating patients 

not as individuals, but as members 

of large homogeneous groups, Lehrach 

said. Now that sequencing costs are falling 

and speeds are increasing, we must 

develop virtual patient systems taking 

into account data from mutation data- 

bases, genomics, tumor sequencing, and 

more. Lehrach compared the models to 

crash models employed by the automobile 

industry. We don’t run crash simulations 

with real people, he pointed out, and 

called for similar models to find optimal 

treatments for patients. 

A trial is currently underway to test 

the models with the ITFoM (IT Future 

of Medicine) project. The goal, Lehrach 

said, is to define a reference model, then 

use many technologies to individualize 

those models. Within ten years, he believes 

such models will be able to lead to 

advances in cancer and metabolic disease. 

He acknowledges that the compute 

requirements for such models will be 

huge—he estimates a petaflop required 

for each patient—but the effort currently 

has support from IBM, Amazon, Siemens, 

Intel, COSBi, and other computing powerhouses 

involved in the ITFoM project 

(see, “Hans Lehrach’s Predictive Biology 

Philosophy,” Bio•IT World, May 2009). 

Connected to that project, Corrado 

Priami, CEO of Microsoft’s Center for 

Computational and Systems Biology 

Center (COSBi) in Trento, Italy, argued 

for the need for a new language to describe 

how biology works, and it just may 

be a programming language. We are trying 

to help biologists “program without 

knowing they are programming,” said 

Priami. 

Priami presented an option for modeling 

a biological pathway using an interface 

based on natural language to explain 

a biological system. The model is easier to 

write, change, and reuse than traditional 

mathematical approaches, though it may 

be slower than classical equations for 

smaller systems. 

Science as a Service 

In the cloud forecast, Folker Myer (Argonne 

National Laboratory/University 

of Chicago) sees the cloud as part of a 

solution, but not the end. Myer defines 

“cloud” as basically grid computing with 

virtual machines, though he acknowledg- 


CONTENTS

CONTENTS 

ROB WHITROW 


University of Manchester’s Carole Goble 

es that “cloud” now includes infrastructure-as-a-service 

(Iaas), platform–as-aservice 

(PaaS), and software-as-a-service 

(SaaS). Myer’s group applies the cloud as 

a solution to huge metagenomics problems 

(the Earth Microbiome Project plans 

to collect 200,000 samples). MG-RAST 

(http://metagenomics.anl.gov), Argonne 

National Lab’s open source metagenomics 

analysis server, was released for the 

cloud in March. 

But the cloud cannot be the only answer. 

When sequencing massive datasets, 

the compute cost is now surpassing the 

sequencing costs, Myer said. Using a 

2009 example, Myer reported that Illumina 

HiSeq 2000 data, running BLAST- 

X on soil samples, could cost $45,000 

for the sequencing and $900,000 for 

the Amazon EC2 computing costs (not 

including storage or data storage). 

Myer believes researchers should 

share results to minimize re-computing 

costs and raw data to minimize data access 

problems. The Open Source Data 

Framework (OSDF), which Myer’s group 

announced in late September, could help 

fix the data analysis problem, he said. 

The Argonne Workflow Engine—a 

RESTful interface with Google’s v8 JA- 

VAscript engine—could also help. It has 

been running MG-RAST for the last 18 

months, and scaling up by 600x. AWE 

distributes work across a number resources 

including HPC clusters, clouds, 

and systems with accelerators (GPUs or 

FPGAs). 


But what does a cloud solution look 

like for labs without HPC clusters or massive 

budgets? The concern voiced by University 

of Manchester’s Carole Goble 

(see, “Democratizing Informatics for 

the ‘Long Tail’ Scientist,” Bio•IT World, 

March 2011) is not big pharma’s use of 

the cloud, but how small academic labs 

can use the resource. Researchers with 

limited funding options or access to large 

computer clusters, already dependent on 

open-source software solutions, have the 

ability to sequence, but need help with 

annotation. 

And so Goble decided to do the “most 

naïve thing you could imagine”—she 

and her team moved her open-source 

workflow platform, Taverna, to the cloud. 

Annotation is perfect for the cloud, Goble 

said. It’s highly repetitive and deeply 

parallel. It works well on a pay-as-you-go 

model. Her goal was to provide annotation 

as a cloud service—science–as-a-service. 

The experiment took four days and 

cost $600 to set up a Web interface and 

test Taverna in the AWS environment. 

The cost per run? $5 and less than two 

hours. She and her team used datasets 

from researchers who are comparing 

why some African breeds of cattle seem 

much heartier than others. The researchers 

were able to use Taverna in the cloud 

to annotate the Boran and Cape Buffalo 

genomes in a couple of hours. 

Goble said the experiment did expose 

some challenges. First, Eucalyptus clouds 

(an open source platform for building 

private clouds) are not the same as AWS. 

Users can not save development costs 

by testing in Eucalyptus clouds before 

moving to AWS—it just won’t work. But 

the bigger problem Goble uncovered was 

that the reference dataset the researchers 

wanted to use was located in the US Amazon 

space, while their work was being 

done in the EU Amazon space. 

“This is a social problem!” Goble 

said. Public databases must exist in the 

cloud, but “just the West coast zone is 

not enough.” The set up raises many data 

ownership issues. Goble’s next crusade 

is to convince major cloud providers 

including Amazon to host public data 

sets for little money so that researchers 

worldwide can easily access and work 

with the data. • 

Briefs 

2012 BEST PRACTICES CALL FOR 

ENTRIES ANNOUNCED 

The 2012 Bio•IT World Best Practices 

competition has released its call for 

entries. Since 2003, Bio•IT World’s 

Best Practices competition has been 

recognizing outstanding examples 

of technology and strategic innovation 

initiatives across the drug discovery 

enterprise. The deadline for 

entry in the 2012 program is January 

13, 2012, and the early bird deadline 

is December 16, 2011. Entries will be 

accepted in six categories: Clinical 

& Health-IT; IT infrastructure/HPC; 

Informatics; Knowledge Management; 

Research & Drug Discovery; 

and Personalized & Translational 

Medicine. 

ILLUMINA INVESTS IN 

GENOLOGICS 

Illumina has led an $8 million 

funding round in GenoLogics, the 

maker of LIMS (Laboratory Information 

Management System) software 

designed for next-generation 

genomics labs. The financing will 

be used to accelerate GenoLogics’ 

product development to support 

future clinical applications and 

new desktop sequencing systems, 

and to expand sales and marketing 

functions. 

BGI AND UC DAVIS LAUNCH 

JOINT GENOME CENTER 

The University of California, Davis, 

and BGI have signed an agreement 

to establish a state-of-the-art BGI 

sequencing facility on the UC Davis 

Health System campus in Sacramento, 

and initiate planning for 

a permanent BGI@UC Davis Joint 

Genome Center. The facility will be 

used to support research initiatives 

in human and animal health, food 

safety and security, biology, and 

the environment. When complete, 

the permanent center will occupy 

about 10,000 square feet on the 

health system campus in Sacramento, 

and will increase UC Davis’ 

sequencing capability approximately 

tenfold.

SGI ® Accelerates Drug Development Pipeline 

at The Institute of Cancer Research 

Overview 

Founded in 1909, The Institute of Cancer 

Research (ICR) is now at the forefront of 

international cancer research with approximately 

1,100 internationally renowned 

staff. Requiring high-performance big 

memory supercomputers, superclusters, 

multi-tiered storage design, and applications 

expertise to process its growing 

research requirements, the ICR has 

chosen SGI® to provide comprehensive 

server and storage solutions. 

Business Challenge 

The ICR focuses on molecular pathology, 

therapeutic development, and genetic 

epidemiology, including studying basic 

molecular and cell biology to identify 

new strategies for cancer therapeutics. 

These studies are used to identify new 

targets for drug development. Increasing 

availability and advances in technology 

have created the challenge of processing, 

analyzing, and storing massive volumes 

of cancer-relevant data. The SGI solution 

addresses this comprehensive challenge 

in a manner that allows researchers to 

focus their full efforts on science, rather 

than on the supporting IT infrastructure. 

Portfolio of SGI Solutions 

Drives Productivity 

The ICR currently utilizes SGI UV shared 

memory supercomputers and several 

SGI ICE clusters on Intel® Xeon® processors, 

and a fully integrated, multi-tiered 

storage design. 

The SGI UV uniquely enables extremely 

large and heterogeneous data to be 

integrated swiftly, allowing researchers 

to correlate data from patient to cancer 

cells on an unprecedented scale. The 

genome assembly algorithms that build 

the final sequences are all memorylimited; 

thus, large shared memory is 

critical in accelerating the workflows in 

this area. Ultimately, this research is 

leading to models that can be used in 

drug development. 

The Institute relies on SGI ICE for 

high throughput image analysis (e.g., 

image processing, recognition, and feature 

extractions) and implementation 

BIO-IT WORLD ADVERTISING SPONSOR 

“ 

The rapidly expanding data requirements within systems 

biology has made large, shared memory essential. Images and 

sequence data results are increasingly converging, indicating a 

growing need for cross-industry collaborations. The SGI solution 

facilitates this by drawing on large memory capacity, enabling us 

to manage data at a higher speed and with greater focus.” 

of machine-learning algorithms on very 

high dimensional datasets, as well as 

for developing database structures for 

data integration. 

As there are several systems stationed 

throughout the U.K., the ICR also needed 

a comprehensive, mirrored storage solution. 

The SGI CXFS shared file system 

and DMF tier virtualization products are 

used at headquarters to ensure that storage 

capacity utilization is optimized and all 

data is easily accessible. Dedicated Parallel 

Data Movers work at both ICR sites 

to and from tier 2 (SGI COPAN) and tier 

3 (LTO 5 tape) storage, depending upon 

the criticality and timeliness of the data 

being processed. Automatic redundancy 

is built in, providing both reliability and 

security. SGI DMF management system 

also enables the ICR to have the option 

of scaling its existing infrastructure in 

the future. 

Business Results 

The ICR’s server and data requirements 

highlight the growing demand for scal- 

— Professor Chris Marshall, Director of Research, ICR 

ability and power within the scientific 

research field. Aside from the need to 

manage and analyze hundreds of terabytes 

of data, the ICR needs to be able 

to perform rapid calculations across a 

broad range of research in a way that 

is cost effective and requires as little 

human input and intervention as possible. 

The entire SGI solution enables 

the ICR to systematically process and 

correlate its growing data requirements, 

providing a system that is essential to 

the future of integrative biology and the 

subsequent development of human 

disease therapies. 

www.sgi.com/go/bio-it 

www.bio-itworld.com NOVEMBER | DECEMBER 2011 BIO•IT WORLD [ 13 ]

CONTENTS 


New Technologies for Patient-Physician 

Interaction at Medicine 2.0 

Social media options 

growing for health. 

BY MING GUO 

PALO ALTO—What if you had access 

to the advice of a real doctor, anytime, 

anywhere? Better yet, what if the advice 

was tailored to your personal situation? 

A web-based medical consultation company, 

HealthTap, is leading the way in 

bridging the communication gap among 

patients and physicians. 

At the recent Medicine 2.0 conference* 

held at Stanford University, Ron 

Gutman, founder and CEO of HealthTap, 

announced the enrollment of 5,000 physicians 

in his online medical consultation 

platform. Coming from a family of physicians, 

Gutman strongly advocates “interactive 

health”—helping patients reach 

physicians, which in turn helps physicians 

“do good in the world.” 

“Medicine is more than 50% art,” he 

said. “Better information is not better 

health. The idea is not to finish everything 

*Medicine 2.0, Stanford University, September 16-18, 2011 


on the Internet, but to find information, 

reduce anxiety, and interact with more 

people in the process of health care.” 

While striving to have the most userfriendly 

interface, the key strength of the 

platform lies in the strong informatics 

technology operating behind the scenes. 

The company has developed robust ontologies 

to organize medical knowledge 

in a way that is both flexible and easily 

extended to different disease verticals. 

“This ontology at the back-end helps 

to direct the right question to the right 

doctor, learn about the patient, and make 

answers tailored to the patient,” said 

Gutman. 

Leveraging the network effect of social 

media, the platform allows physicians 

around the world to share their most 

up-to-date information. Those whose 

information is most agreed upon receive 

higher scores, which helps establish a better 

online reputation. 

Although the current platform does 

not allow 1-on-1 private consultations, 

HealthTap is in the process of creating 

a more secure HIPAA-compliant 

environment to allow physician-patient 

interactions. 

Around the Bay Area, companies 

integrating health information with 

social networks seem to be booming. 

Healthism.com is designed to “push the 

envelope even further by developing 

the world’s first effective social network 

custom-built to inspire lifestyle changes 

by transforming advice into action,” said 

CEO Damon Ramsey. 

Another online platform for patient-to-patient 

information sharing 

in the Crohn’s and Colitis community 

is Crohnology.com. Its founder, Sean 

Ahrens, talked about “demoing Crohnology.” 

After the conference, his blog post 

about was viewed by more than 15,000 

people overnight. “There is clearly a pentup 

need by patients around the globe for a 

site like Crohnology,” Ahrens said. 

In the “Medicine 2.0” era, information-empowered 

patients will take charge 

of their own health care within the ever 

more connected physician-patient network. 

While issues like reimbursement 

may take time to be sorted out, Medicine 

2.0 is nevertheless giving more attention 

to “care” in the health care equation, and 

putting the individual back into personalized 

health care. • 

And the Winner Is... 

The NGS Data Interpretation survey in 

the last issue of Bio•IT World received an 

overwhelming response. 

The winner of the Kindle is: 

Alan H. Christensen 

Associate Professor 

George Mason University 

Thank you for your time, and we invite 

you to participate in future surveys. 

Kevin Davies 

Editor-In-Chief

Up Front The Bush Doctrine 

Another 

Cloudy Day? 

ERNIE BUSH 

Cloud computing certainly deserves the prize for most 

talked about (most hyped?) computing development 

of the new decade. Even my 84-year-old Mother recently 

made a joke about moving her work into the 

cloud in the foreseeable future, although I am sure 

she is clueless about any technical meaning behind 

the phrase. Unfortunately, as with all newly-minted concepts 

and jargon, the exact interpretation or instantiation of “cloud 

computing” is still highly dependent on who is expressing the 

opinions. Still, the core idea and vision for cloud computing has 

definitely gelled to the point where all businesses can have intelligent 

discussions around if, and how, this new tool set could 

add value to their enterprise. 

Cloud Computing in a Regulated Environment 

Perhaps the key hallmark of pre-clinical safety assessment that 

differentiates it from all other forms of non-human research 

activities is that much of this work is conducted under the 

strict oversight mandated by Federal Good Laboratory Practice 

(GLP) regulations. These Code of Federal Regulation directives 

provide clear expectations for security, traceability, and validation/qualification 

of software products and therefore the natural 

question becomes: Is there a place for cloud computing in a 

GLP environment? 

Clearly others are much more qualified to discuss and pontificate 

over the technical details and merits of cloud computing 

in a GLP environment, so this column will focus on the 

perceived advantages/disadvantages such a tool set could offer 

from the perspective of one that had the responsibility to make 

the business of GLP safety assessment as high quality and yet 

as cost effective as possible. There was a time in my career 

when pharmaceutical pre-clinical safety assessment had an air 

of “spare no expense”. While we certainly did not have a blank 

check, we did have a lot of resources and funding to do the job 

right. However with all the cost cutting pressures on pharma 

these days, this mandate for “quality at any cost” has certainly 

been muted. This pressure for cost containment has progressed 

to the point where many pharmas—even very large pharmas— 

have completely discontinued all GLP operations in-house and 

now conduct these studies at Contract Research Organizations 

(an unimaginable development when I entered the business 

nearly 30 years ago). Overall I do not see this migration of GLP 

into the out-sourcing and off-shoring arena as a significant 

loss to the integrity of early safety assessment, but I do wonder 

about what this commoditization of safety assessment means in 

terms of retaining in-house expertise. 

Therefore, given both the need to manage costs and the 

need to maintain fundamental or firsthand experience with a 

required element of new drug development, one could ask what 

does cloud computing bring to the table? And the overwhelming 

answer is of course saving the incredible costs that GLP 

safety assessment organizations currently invest in purchasing, 

qualifying and maintaining extensive IT infrastructures to support 

their regulated studies. In my career I have often marveled 

at how much time and money we spend on these IT issues (actually 

just the time spent arguing about these IT issues) and the 

idea that I could simply contract this out to some cloud-based 

(cloudy?) service provider sounds nearly irresistible to me. On 

the other hand, when asked what would be my major concern 

about moving to such a cloud-based system it would have to be 

security. Again, the traditional view of preclinical safety data 

was that they were an essential element of the family jewels 

and as such needed to have a level of protection befitting that 

status. Therefore the question 

There are strong 

business reasons 

to consider or 

avoid cloud-based 

services in a GLP 

environment. 

becomes: can cloud-based solutions 

be as—or even more— 

secure than in-house data 

systems? I have heard both 

pro and con arguments on that 

position, but I must say the 

rather constant drum beat of 

security breaches at financial 

institutions gives me reason to 

worry. 

So it would appear there 

are strong and compelling business reasons to consider or avoid 

cloud-based services in a GLP environment. But what would 

keep me up at night would not be the question of whether we 

can achieve a certain level of cost savings or maintain appropriate 

levels of security and integrity. Rather it would be whether 

we had yet again fallen victim to the hyped-up rhetoric surrounding 

the introduction of new technology. In my experience 

only about 1 in 10 new technology introductions actually end 

up having a truly positive or game-changing impact over the 

long haul. Most new technologies (say 5 or 6 of 10) end up offering 

some advantages and some disadvantages and therefore 

sum up to a low or zero net impact. And some, on the order of 

2 of 10, actually end up costing us more than we recovered in 

benefit. Will “cloudy” solutions be that 1 in 10 big leap forward, 

or are they just another resource drain whose benefits never 

live up to their sunny promise? 

Ernie Bush is VP and Scientific Director of Cambridge Healthtech 

Associates. Email. ebush@chacorporate.com 


CONTENTS

CONTENTS 

The Skeptical Outsider 

Science in Thrall 

to the FDA 

BILL FREZZA 

Risk aversion is the inherent enemy of progress. In a 

free society we can each seek our own balance, accepting 

the consequences. But when entrenched interests 

are allowed to thwart attempts by innovators 

and entrepreneurs to challenge the status quo, we 

all pay the price. As America slides into malaise and 

decline, nowhere is this more evident than in our passive acceptance 

of the absolute power of the U.S. Food and Drug Administration—even 

in the face of certain death. It need not be so. 

Forty years after President Richard Nixon declared War on 

Cancer—one of the most expensive and protracted wars in U.S. 

history—it’s hard not to be discouraged. If you should be unfortunate 

enough to be diagnosed with ovarian cancer, you are 

going to die. Same for pancreatic cancer. Or lung cancer. Not to 

mention a host of other metastatic sarcomas that medical science 

has not yet conquered. 

Who hasn’t lost a friend or family member to the Emperor 

of all Maladies? Who hasn’t watched victims struggle with false 

hopes raised by palliative remedies that a quick Google search 

will tell you can at best delay the inevitable? And who hasn’t 

imagined that if fate were to put them in a similar circumstance 

they would accept the risk of an experimental alternative on the 

chance of a cure, however slim? 

Yet standing between overburdened innovators and willing 

patients is an unaccountable agency determined to enforce 

a standard of safety completely disproportionate to the dire 

circumstances of the terminally ill. Exactly where in the Constitution 

did the people confer such power over life and death on 

unelected bureaucrats? 

Initially established by the Pure Food and Drug Act of 1906, 

the U.S. Department of Agriculture was granted the power 

to seize adulterated or misbranded food as well as mislabeled 

drugs when shipped across state lines. Note the constitutional 

foot in the door. In 1911, attempts to expand the USDA’s authority 

to regulate drug efficacy were struck down by the Supreme 

Court, slowing but not stopping the steady accretion of power. 

By the time the New Deal finished eviscerating most constitutional 

limitations, the FDA was born. 

A report recently released by the Milken Institute—“The 

Global Biomedical Industry: Preserving US Leadership”—documents 

how the wheels of progress have been slowly grinding 


to a halt as the FDA raises the bar for drug approval. The length 

of time required to complete clinical trials over the past decade 

is up 70%. The median number of procedures required per trial 

is up 50%, as is the total work burden per protocol. Meanwhile, 

volunteer enrollment and retention has been driven down by 

21% and 30% respectively. And, of course, new drug approvals 

are down 50%. Keep this up and it won’t be long before clinical 

trials follow U.S. manufacturing to China, with other elements 

of the pharmaceutical industry trailing closely behind. 

Even as trials drag on with preliminary information kept 

blinded, new laboratory developments that could improve 

results are banned due to an insistence on maintaining rigid 

conformity to outdated protocols. In what other industry does 

this happen? The calls for “adaptive trials” that might be more 

suitable in an age of personalized medicine remain unheeded. 

And the shameful spectacle of denying Americans access to 

drugs that are approved and available in Europe and elsewhere 

defies justification. 

Is there an alternative? 

While wholesale FDA reform is needed, doing it right would 

entail a monumental effort that could take years. But there are 

modest steps we can take in the meantime. How about carving 

out one or more FDA-free Enterprise Zones where doctors, 

scientists, and volunteer patients can make their own decisions 

unfettered by the heavy hand of regulators? Imagine an experimental 

terminal-illness wing of the Cleveland Clinic where informed 

consent was the only law. How hard would it be to draft 

enabling legislation? 

Defenders of the FDA’s prerogatives would fight such proposals 

tooth and nail. But what kind of nanny state arguments 

can be made against conducting such a policy experiment when 

anyone who objects doesn’t have to be treated? Breakthroughs 

that emerge would still have to pass through the FDA gantlet 

before they would be generally available. The difference is that 

researchers could continue making improvements while treating 

volunteers during this long process. 

If we fail to arrest the regulatory assault on medical progress 

in the U.S., sooner or later out-of-the-box solutions like the one 

described above will pop up—elsewhere. And American patients 

will follow. The price of a plane ticket is trivial compared 

to the cost and consequences of cancer. Perhaps if enough patients 

start voting with their feet, pressure for change will build 

from those without the means to take care decisions into their 

own hands. 

But it should never come to that. There is no good reason 

we shouldn’t have access to the most advanced treatments at 

home. First, however, we need to exercise the political will to 

demand our right to choose. Are we up to the challenge? 

Bill Frezza is a fellow at the Competitive Enterprise Institute 

and a Boston-based venture capitalist. He can be reached at 

waf@acm.com.

Insights | Outlook 

NGS by the 

Numbers 

LAURIE SULLIVAN 

Insight Pharma Reports conducted a user market survey 

as part of its latest report focused on next-generation 

sequencing (NGS), which describes innovations in this 

field and analyzes their impact on what can only be described 

as an extremely dynamic technology and market 

sector. Partial survey results are shared here. 

Respondents were asked to rate sequencer attributes on a 

scale of 1–5 (with 5 being most important; see Table). Average 

response ratings are proportional to the relative importance of 

an attribute. Results show a great deal of bunching 

in the 3–4-point range, which indicates that those attributes 

are considered well above average in importance. 

However, a few points stand out. “Instrument 

size” rates considerably lower in importance than any 

other factor within this survey population, which is 

weighted strongly toward modest-sized, academic 

core labs. Also noteworthy are raw data accuracy and 

consensus accuracy, both of which have the highest 

importance ratings. 

This observation is not surprising given the predominance 

of genetic variation studies among user 

applications. It is interesting in this respect that, in 

our PacBio interview (excerpted in the September/ 

October issue of Bio•IT World), Dr. Steven Turner 

claims that long-read tails in repetitive SMRT sequencing 

of single-molecule fragments can compensate 

for relatively low raw read accuracy and generate 

very high consensus accuracy. 

Selling Points 

We also asked whether a respondents’ organization had purchased 

a low-cost NGS system or planned to do so by the end of 

2011. In fact, more than half (56%) answered positively. 

In terms of system selection among the three such systems 

available, Ion Torrent’s PGM came in first (59.2%), the new Illumina 

MiSeq second at 26.5%, and the 454 GS Junior at 14.3%. 

Next we asked whether organizations are currently doing 

single-molecule sequencing using one of the two commercially 

available systems. Only one-fifth of those surveyed responded 

to this question, and nearly three-quarters of those use Pacific 

Biosciences’ RS system compared to one-quarter using Helicos’. 

When asked whether their organization planned to purchase 

a Pacific Biosciences’ sequencer in the coming year, 

a surprisingly-high 20% of the 71 respondents answered 

affirmatively. 

An additional query along this same line asked about degree 

of interest in performing single-molecule sequencing. Given 

five degrees of interest, 85% of the 68 responses fell in the top 

three categories, with roughly equivalent numbers for ‘very 

much,’ ‘quite a lot,’ and ‘moderately.’ 

The next two queries dealt with nanopore-based singlemolecule 

sequencing. The first asked respondents’ opinion on 

the likelihood that a nanopore system would hit the market 

by the end of 2012, given four levels of response covering ‘very 

likely,’ ‘somewhat likely,’ ‘possible,’ and ‘unlikely.’ The largest 

number of responses fell in the ‘possible’ category, although 

about one-quarter fell in each of the two more likely categories. 

Only 13% thought it unlikely. The result reflects somewhat 

more optimism than conclusions drawn by individuals whom 

we interviewed, who tended to believe that once feasibility for 

sequencing was made public, several more years would need to 

elapse before commercial introduction. 

Sequencer Attribute Rankings 

Chart shows the number of respondents that gave each category a 1-5 ranking, along with the 

average for each category and the total number of responses. 

Category 1 2 3 4 5 Avg. Count 

Instrument size 19 26 17 6 5 2.34 73 

Instrument cost 4 7 21 21 22 3.67 75 

Raw data accuracy 4 2 4 25 40 4.27 75 

Consensus accuracy 2 3 3 25 39 4.33 72 

Read length 2 4 11 35 24 3.99 76 

Output per time 3 10 19 27 16 3.57 75 

Overall run time 4 6 27 28 9 3.43 74 

Prep time 3 6 29 24 12 3.49 74 

Sequencing time 3 11 20 32 9 3.44 75 

Informatics time 0 10 13 32 19 3.81 74 

Source: Insight Pharma Reports 

Respondents’ were then asked to rate attributes of a putative 

nanopore system on an attractiveness scale of 1–5, with 5 

reflecting most important. Again, the average score is proportional 

to attractiveness. Read length and accuracy both led with 

scores exceeding 4, followed closely by speed and consumables 

cost. Instrument cost and size fell last in the attractiveness 

scale, both with scores less than 3.4. 

For complete survey results, as well as transcripts of interviews conducted 

with individuals highly knowledgeable in diverse aspects of NGS, please refer to the 

full Insight Pharma Report: Next-Generation Sequencing Generates Momentum: 

Markets Respond to Technology and Innovation Advances. July 2011. 

www.InsightPharmaReports.com 


CONTENTS

ConCurrEnT TraCks: 

1 IT Infrastructure – Hardware 

2 IT Infrastructure – Software 

3 Cloud Computing 

4 Bioinformatics 

5 Next-Generation Sequencing 

Informatics 

6 Systems and Multiscale Biology 

7 eClinical Solutions 

8 eHealth and HIT Solutions for 

Personalized Medicine 

9 Drug Discovery Informatics 

EvEnT FEaTurEs: 

Access All 12 Tracks for One Price 

Network with 2,000+ Global Attendees 

Hear 125+ Technology and Scientific 

Presentations 

Connect with Attendees Using CHI’s Intro-Net 

Choose from 14 Pre-Conference Workshops 

Organized by: 

Cambridge Healthtech Institute 

Cambridge Healthtech Inst itute’s Eleventh Annual 

10 Molecular Diagnostics Informatics NEW! 

11 Open Source Solutions NEW! 

12 Cancer Informatics NEW! 

CONFERENCE & EXPO ’12 

Enabling Technology. Leveraging Data. Transforming Medicine. 

kEynoTE PrEsEnTaTIons By: 

Eric D. Perakslis, Ph.D., 

Chief Information Officer and Chief 

Scientist of Informatics, U.S. Food 

and Drug Administration 

Martin Leach, Ph.D., 

Chief Information Officer, 

Broad Institute of MIT 

and Harvard 

Jill P. Mesirov, Ph.D., 

Associate Director, Chief Informatics 

Officer; Director, Computational 

Biology and Bioinformatics, Broad 

Institute of MIT and Harvard 

See the Winners of the following 

2012 Awards: Benjamin Franklin, 

Best of Show, and Best Practices 

View Novel Technologies and Solutions 

in the Expansive Exhibit Hall 

And Much More! 

Bio-ITWorldExpo.com 

Platinum Sponsors: 

Official Publication: 

register by 

December 9 

and save 

up to $600!

2012 Bio-IT World Conference and Expo speakers (partial list as of October 2011) 

Joe Acciavatti, Director, Operations and Communications, 

MONOC 

Michael J. Ackerman, Ph.D., Office for High Performance 

Computing and Communications, National Library 

of Medicine 

Peter Sejer Andersen, Director, Antibody Discovery, 

Symphogen 

Bjorn Andersson, Director of Solutions Marketing, BlueArc 

Mark Apgar, Senior Manager, Clinical Informatics, Allergan 

Sandy Aronson, Executive Director, IT , Partners HealthCare 

Center for Personalized Genetic Medicine 

Alex Bangs, CIO, Crescendo Bioscience 

William K. Barnett, Ph.D., Director, Science Community Tools, 

Research Technologies, Indiana University 

Toby Bloom, Ph.D., Director, Informatics, Genome 

Sequencing, Broad Institute 

Jeffrey Brown, Ph.D., Assistant Professor, Population 

Medicine, Harvard Pilgrim Health Care Institute/ Harvard 

Medical School 

Zhaohui (John) Cai, Director, AstraZeneca 

Michael Cantor, M.D., Senior Director, Biomedical 

Informatics Services, Pfizer, Assistant Professor of Medicine, 

NYU Medical Center 

Leonard D’Avolio, Ph.D., Associate Center Director, 

Biomedical Informatics, MAVERIC, Department of 

Veterans Affairs 

Chinh Dang, Senior Director, Technology, Allen Institute for 

Brain Science 

Ramin Daron, IT Director, Information Technology, Johnson 

& Johnson 

Bernd Doetzkies, Director, Informatics, Daiichi Sankyo 

Pharma Development 

David J. Dooling, Ph.D., Assistant Director, The Genome 

Center, Washington University, St. Louis 

Chuanbin Du, Ph.D., Post-Doctoral Fellow, Bioinformatics and 

Genomics, University North Carolina-Charlotte 

Yaniv Erlich, Ph.D., Principal Investigator, Whitehead Fellow, 

Whitehead Institute for Biomedical Research 

James Ewen, Business Analyst, Research Informatics & 

Automation, Bristol-Myers Squibb Company 

Christopher Farah, Bioinformatics Systems and Software 

Specialist, Maine Institute for Human Genetics and Health, 

Eastern Maine Healthcare Systems 

Jacob Farmer, Chief Technology Officer, Cambridge Computer 

Norbert Fritz, Development Leader Business Information 

Warehouse, Pharma Operations, PDGI, F. Hoffmann-La 

Roche Ltd. 

Rich Furr, Head, Global Regulatory Affairs and Chief 

Compliance Officer, Staff, SAFE-BioPharma Association 

Ray Fyhr, Project Lead, MRL-IT, Merck 

Christine Gibson, Associate Director, Clinical Business 

Systems, Biogen Idec 

Robert Gottlieb, Principal, RMG Associates, LLC 

Andrew Grygiel, Vice President, Product Management, 

ClearTrial 

Jian Han, Ph.D., Faculty Investigator, Hudson Alpha Institute 

for Biotechnology 

Paul A. Harris, PhD, Director, Office of Research Informatics 

Operations, Associate Professor, Department of Biomedical 

Informatics, Department of Biomedical Engineering, 

Vanderbilt University 

Sifei He, Beijing Genome Institute 

Joe Herring, CEO & Chairman of Covance 

Mark Hulse, R.N., Vice President, Information Technology, 

Chief Information Officer, Moffitt Cancer Center 

Xin Jin, Beijing Genome Institute 

Jason Johnson, Executive Director, Informatics IT, Merck 

Khodaberdi Kalavi, Ph.D., Faculty, Lab. Medicine, Molecular 

Medicine, Golestan University of Medical Sciences 

Aaron Kamauu, M.D., CEO, Healthcare Data Analytics, 

Anolinx LLC; former Head, Healthcare Data Strategy, Roche 

and Genentech 

Randy King, Ph.D., M.D., Associate Professor, Department of 

Cell Biology, Harvard Medical School 

Isaac (Zak) Kohane, M.D., Ph.D., Director, Children’s Hospital 

Informatics Program; Henderson Professor of Pediatrics and 

Health Sciences and Technology, Harvard Medical School 

(HMS); Co-director, HMS Center for Biomedical Informatics 

and Director of the HMS Countway Library of Medicine 

Michael Kopach, Ph.D., Research Advisor, Chemical Product 

Research and Development, Eli Lilly and Company 

Serdar Kurtkaya, Software Engineer, Chemistry, Emory 

Institute for Drug Discovery 

Steve Labkoff, MD, FACP, Head of Strategic Programs, 

AstraZeneca Pharmaceuticals LP 

Janis E. Landry-Lane, Program Director, World-wide Deep 

Computing , Life Sciences/ Higher Education Segments, IBM 

Jason M. Laramie, Ph.D., Principal Application Scientist, 

Complete Genomics, Inc. 

Anthony Leotta, Bioinformatics Manager, Cold Spring 

Harbor Laboratory 

Roger (Rangjiao) Liu, Ph.D., Research Manager of 

Bioinformatics, Life Science Development, Corning 

Victor Lobanov, Ph.D., Director, Informatics Center of 

Excellence, Johnson & Johnson 

Ravi Madduri, Fellow, Computation Institute, University of 

Chicago and Argonne National Lab 

Raymond Ng, Ph.D., CIO, Computer Science, PROOF Centre 

Chris Petersen, CIO and Founder, Assay Depot 

Tibor van Rooij, Faculty of Pharmacy and Pharmaceutical 

Sciences, University of Alberta; former Director, 

Bioinformatics, Génome Québec and Montreal Heart Institute 

Pharmacogenomics Centre 

Vishal Rosha, Senior Scientist, Bioprocess R&D, Novartis 

Pharma Ag 

Anthony Rowe, Ph.D., Principle Scientist - External 

Innovation, R&D IT, Janssen 

Jared Shockcor, Domain Architect, Research Informatics & 

Automation, Bristol-Myers Squibb Company 

Alex Sherman, Director, Systems, Department of Neurology, 

Massachusetts General Hospital 

Juswinder Singh, Ph.D., Founder & CSO, Avila 

Therapeutics Inc. 

Timothy Swaller, Director, Information Technology and 

Genomics, Ceres, Inc. 

Peter J. Tonellato, Ph.D., Visiting Professor, Senior Research 

Scientist, Pathology, BIDMC & Center for Biomedical 

Informatics, Harvard Medical School 

Laszlo Vasko, Director, R&D Information, AstraZeneca 

Vas Vasiliadis, Director, Products, Computation Institute, 

University of Chicago 

Xiaoming Wang, Ph.D. Fellow, Computation Institute, 

University of Chicago and Argonne National Laboratory 

Andrew Witty, CEO, GlaxoSmithKline 

Elizabeth Worthey, Ph.D., Assistant Professor, Human and 

Molecular Genetics Center, Department of Pediatrics, 

Bioinformatics Program, Medical College of Wisconsin 

Wenming Xiao, Ph.D., Staff Scientist, Division of 

Computational Biology, Center for Information Technology, 

National Institutes of Health 

Lixia Yao, Ph.D., Investigator, Computational Biology, 

Quantitative Sciences, GlaxoSmithKline 

Alexander Wait Zaranek, Ph.D., Director of Informatics, 

Harvard Personal Genome Project, Genetics, Harvard 

Medical School 

For more speaker additions, please visit: 

Bio-ITWorldExpo.com


Sustainable Science: Energy Efficient 

Computing for Biosciences 

Illustration of the RIVYERA reconfigurable computer for high performance analysis 

By Tim Pietruck 

Moore’s Law, the observation that 

the speed of computers tends 

to double every 18 months, is 

common knowledge. For scientists and ITexperts, 

it is also common knowledge that 

the increase in biological data generation 

outpaces Moore’s law by far. From next 

generation sequencing to high-throughput 

imaging, improvements in technology 

and widened analysis-scope put a high 

workload on researchers’ IT infrastructure. 

One might even say that it is turning 

life-sciences into information- rather than 

natural-sciences. 

It is no surprise that many professionals 

are searching for ways to manage 

this expanding gap between biological 

research possibilities — and the increase 

in data should be seen as a possibility 

rather than a burden — and realistically 

attainable processing resources. One 

approach has been the thoroughly hyped 

cloud-computing with all its benefits and 

drawbacks. Another trend, somewhat less 

omni-present but more efficient in solving 

infrastructural bottlenecks, is the computation 

acceleration with dedicated hardware. 

Here, the options are many — ranging 

from consumer graphics 

cards to millions of dollars 

expensive ASIC production. 

In between those extremes, 

Field-Programmable Gate 

Arrays (FPGAs) promise to 

provide the most favorable 

combination of reconfigurability 

for changing scientific 

requirements and processing 

power per dollar spent. 

Indeed, cost is increasingly 

important when it comes 

to strained research budgets, 

in terms of purchasing 

IT-equipment but also maintenance, 

electricity and cooling. Especially with 

increasing electricity prices, a total-cost-ofownership 

approach is needed for investment 

decisions. Energy- and therefore 



cost-efficient solutions are in increasingly 

high demand and FPGAs, with a few watts 

of energy consumption per processor fit 

exactly this description. 

FPGA-computing is not a brand-new 

concept, but only recently have companies 

like Germany based SciEngines 

made inroads into usability, scalability 

and affordability that promise significant 

practical benefit for a wide audience in 

the sciences. 

Key to this is a standardized platform 

— the RIVYERA computer, which provides 

a scalable architecture for up to 256 midsized 

FPGAs within one regular server. 

For putting this into perspective, please 

refer to below technology comparison. 

Smith Waterman Algorithm — Performance (in GCUPS) 

Cell/BE (8 Threads) 

NVIDIA GTX 295 (Dual-GPU) 

2.66 GHz Nehalem-EP (8 cores) 

RIVYERA 2S6-LX150 (16 FPGAs) 

SGI Altix UV 1000 (384 cores) 

RIVYERA S6-LX150 (128 FPGAs) 

RIVYERA S6-LX150 (256 FPGAs) 

Source: University of Kiel 

16 

30 

32 

756 

986 

6046 

0 3500 7000 10500 14000 

Cell Updates Per Second (in billions) 

The referenced Smith-Waterman algorithm 

is a standard, processing-intensive 

computational task and the optimizable 

structure of FPGAs easily outclasses 

other technologies — even in a version 

that includes affine gap alignment and 

custom scoring matrices. In addition, also 

memory-access focused applications, like 

NGS short read mapping, can be very well 

executed on such a system. PC-workstations, 

no matter if containing single- or 

twelve-core CPUs, and hybrid computers 

are usually limited by access speed to 

a single memory. The RIVYERA provides 

users with access to a large number of 

distributed modules, equal to the number 

of FPGAs, and dedicated lanes from each 

FPGA to optional shared memory. Thus, 

for specific algorithms, the performance 

of a cluster or even a small data-center 

can be provided at the desk-side, and 

new approaches to analysis and science 

become available — for only 

a five digit price-tag. 

SciEngines is currently 

driving the development of 

bioscience-focused FPGA 

solutions and provides 

development resources to 

interested parties. Application 

programming interface 

specifications are freely avail- 

12092 able and the development 

community is supported with 

tools and affordable smallscale 

systems. Please feel 

free to contact the author if 

you would like to get involved. 

Tim Pietruck is Vice-President at SciEngines 

GmbH, a leading manufacturer of FPGA- 

computers for the hpc community. He can 

be reached at timpietruck@sciengines.com


An Inside Perspective 

on PAREXEL 

One of the oldest clinical research organizations 

discusses technology and changes in the industry. 

Mark Goldberg, PAREXEL’s chief operating officer, has been with the company since 

1997 when he started the CRO’s medical imaging business. A radiologist by training, 

Goldberg ran a spin-off company from Massachusetts General Hospital in the 

tele-health space, which he helped to found. In 2000, PAREXEL created its technology 

business, Perceptive Informatics, as a majority-owned subsidiary. As Goldberg says, 

“we believed that it was an industry that grossly under-utilized technology and that 

this was a huge opportunity that would be important.” Believing that it could help 

differentiate their CRO service offerings, and importantly, help biopharmaceutical 

companies get products to market faster, in 2005, PAREXEL brought in Perceptive as 

a wholly-owned subsidiary, seeking greater efficiencies in the development process by 

combining an eClinical platform with clinical expertise. 

Goldberg recently sat down with Bio•IT World chief editor Kevin Davies to discuss 

the importance of convergence in Perceptive’s suite of eClinical offerings, and to share 

his insights on the future opportunities, trends, and challenges facing the industry. 

Bio•IT World: Mark, what were PAREXEL’s 

core services, and how did the company’s 

technologies integrate into the formation 

of Perceptive Informatics? 

GOLDBERG: PAREXEL was one of the first 

clinical research organizations (CROs), 

founded nearly 30 years ago... We were 

born initially as a consulting business to 

help companies outside the U.S. navigate 

the regulatory environment. Eventually 

the company expanded into the core clinical 

research services, including monitoring, 

data management, medical affairs, 

biostatistics, medical writing, and regulatory 

affairs—all the core components of 

running a clinical trial. 

We took the customer-facing technologies 

that existed within PAREXEL 

and rolled them into Perceptive, including 

the medical imaging business and interactive 

voice response systems (IVRS). 

We were also probably the first player 

to launch portal technology in the drug 

development industry. Portal technology 

was already used in other industries, but 

it was new to clinical trial management. 

Today, PAREXEL is a $1.2 billion company 

and most of our revenue generation 

is derived from the conduct of clinical tri- 

als around the world. Perceptive accounts 

for approximately 13% of PAREXEL’s 

total revenue. 

How has Perceptive evolved from its 

imaging roots over the past decade? 

[Imaging] created the basis of our technology 

business. IVRS was introduced 

not only because it made it simpler to randomize 

patients in clinical trials but also 

because it allowed better management of 

investigational drug inventory. 

Historically you would basically put 

a full supply of both the investigational 

product as well as placebo (or comparator) 

at all of the sites, with little ability to 

predict actual need. The amount of waste 

was enormous, because every site was 

treated like its own little repository. Using 

technology, and being able to predict and 

track how patients are randomized at the 

various sites, one could ensure that the 

inventory sent to sites was more appropriate 

to the number and mix of patients 

enrolled. In terms of other technologies, 

we have conducted EDC-based trials 

for many years, and built an industryleading 

clinical trial management system 

(CTMS). 

PAREXEL’s acquisition of ClinPhone 

in 2008 set a number of dominoes in 

motion. We were focused on bringing the 

first interoperable eClinical suite to the 

industry. Standalone systems were not 

well integrated and we saw an opportunity 

to really accelerate development... 

From a procurement standpoint, sponsors 

spent a lot of time trying to understand 

the different tools. The advantage 

was that by doing things electronically 

and eliminating paper, you could shorten 

cycle times by reducing query activity, 

locking databases faster, and so forth. 

But then, as technologies mature and you 

know that they work, the features and 

functionality among competing products 

become fairly similar... 

We use the term convergence when we 

talk about similar trends in the eClinical 

industry. If you enter our eClinical 

suite through one of our applications, 

we expose the functionality of other applications 

without it feeling like you’re 

working with a number of different tools. 

It becomes much easier for the user. You 

can also eliminate extra work on the back 

end that used to occur around reconciling 

databases across the different tools being 

used for a given trial. I don’t know that any 

eClinical suite does absolutely everything, 

but we believe that ours covers the broadest 

waterfront. However it is still important 

for an eClinical suite to be designed 

to link easily with other third-party tools. 


CONTENTS

CONTENTS 


You can never assume everything you have 

is everything you’ll ever need. 

What other services does PAREXEL offer 

and how does technology fit? 

When we are hired to run clinical trials, 

the purchaser is increasingly allowing us 

to make the decisions about what tools we 

should apply to do that work. Historically 

the client might have been very prescriptive 

about using certain technologies. 

Today, it is more likely that they tell us, 

‘We want you to run the program, and 

you have the flexibility to recommend 

the best tools for the job—the ones that 

will deliver the greatest efficiencies.’ In 

that scenario, we have a strategic advantage 

because we have a full technology 

capability in addition to our clinical trial 

execution capability, which is unique to 

the CRO industry. 

That said, we also sell our technology 

to other CROs. In fact, part of the reason 

that we preserve Perceptive as a subsidiary 

is because it makes it somewhat 

easier to support the full range of customers 

in the clinical trial business, including 

sponsors and other CROs. 

Roughly 75% of PAREXEL’s revenue 

is derived from what we call CRS (clinical 

research services). That includes phase 

I through IV development. We offer 

a broad range of services from first in 

human and patient studies in early development 

to core clinical development 

programs, through and including periapproval 

and post-marketing work. As I 

mentioned earlier, Perceptive contributes 

approximately 13% of our total revenue. 

The remaining 12-13% comes from our 

consulting and medical communication 

business. We probably have one of the 

oldest and most respected regulatory consultancies. 

We consult in a broad range 

of areas including strategic compliance, 

product development strategy, and regulatory 

affairs. We also consult in commercialization, 

which incorporates a focus on 

reimbursement and market access. 

What areas do you see for big growth? 

I think there are a couple trends to mention... 

We’ve been fairly provocative in the 

market in terms of our focus on having a 

convergent eClinical solution or suite. It’s 

built upon a platform of technologies that 


allows the various tools to intercommunicate 

readily, and relieves the customer 

of the need to deal with both integration 

work and also the reconciliation of disparate 

databases. 

In our eClinical suite, we have the 

ability to leverage a broad set of solutions. 

This includes our IMPACT CTMS, 

which is still a market leader as well as 

our DataLabs EDC solution. We have 

the ability to provide IVRS for patient 

enrollment and study 

drug management—an 

offering that we refer to 

as RTSM, or random- 

R oughly 75% 

of PAREXEL’s 

revenue is 

derived from 

what we call 

CRS—clinical 

research 

services. 

ization and trial supply 

management—and our 

medical imaging services 

remain a core offering. 

Perceptive does 

a lot of work around 

Web-based reporting 

tools in order to surface 

data from the various 

systems to inform trial 

management and decision 

making. 

We also support 

electronic patient-reported 

outcomes (ePRO), although we 

have elected to avoid the hardware business 

for electronic diaries. Perceptive does 

provide consultation including help with 

design, instrument selection, and regulatory 

considerations. Where appropriate, 

we partner with technology vendors to 

provide whatever modality the client 

many need for data collection. We deliver 

voice based diaries ourselves. 

As a $1.2 billion company, where do you 

go looking for new business? 

We’ve always been a global business... We 

were one of the first to grow into Eastern 

Europe; we have a large presence in Latin 

America and in Africa. And we have one 

of the largest presences in Asia-Pacific, 

partly the result of the acquisition of a 

company called APEX International, 

which was the largest CRO in Asia- 

Pacific, in 2007. 

Are there any downsides to global trials? 

There is certainly complexity. You have to 

be experienced, have the knowledge and 

expertise to know how to execute in these 

various countries. I would say that there 

are a relatively small number of companies, 

like PAREXEL, that are credibly capable 

and have the experience to execute 

on a global scale using standardized processes. 

You have to understand the regulatory 

environment, the import/export 

rules, how medical care is conducted, and 

so on. And you have to have knowledge 

of the investigator community so that 

you know who can deliver quality data 

based upon a track record 

of high performance. The 

sponsor looks to us to be 

able to do a great job of 

selecting top quality investigators 

around the world. 

You have to have experience 

in these geographies 

and local expertise—real 

feet on the street. 

Where are you finding 

new business 

opportunities? 

Strategic partnering is really 

a new trend over the 

last few years, and gaining 

momentum. We are now 

considered a strategic partner of choice 

for a broad range of leading sponsors— 

from large pharmaceutical companies to 

mid-sized and smaller biopharmaceutical 

companies. This industry was historically 

very tactical in the way that it utilized 

outsourcing. In the past, a CRO would be 

called in if the sponsor had a shortage of 

personnel in a certain location or around 

a certain function. However, over time it 

became clear that these tactical relationships 

were fairly inefficient. 

Strategic partnering is characterized 

by relationships where the sponsor will 

select one or two, typically large, global 

CROs, and will agree that their work is 

going to be split between these providers. 

Unlike a tactical relationship, in strategic 

deals ownership and accountability for 

delivery, and participation in design starts 

to become a shared event. It’s not just that 

a sponsor develops a protocol and asks 

the CRO to execute it for them. Now, we 

are involved in working together on the 

strategy, the cost, the trade-offs in terms of 

different countries we could go to, the in- 

(continued on page 25)

Each day security professionals are faced with new enemies, tactics and threats— 

it’s time to evolve your security strategy. RSA® Conference brings you �ve days 

of innovative sessions, inspiring keynotes, and collaborative strategy building. 

Gain insights on today’s hottest topics, learn how to leverage the latest trends and 

technologies, and get access to new best practices on the most critical technical 

and business issues facing you today. 

Join the community at RSA® Conference 2012 to empower yourself with new 

insights, solutions and allies to keep your organization secure. 

REFINE YOUR EXPERTISE 

Participate in over 220+ 

expert-led sessions. 

SHARE YOUR INSIGHTS 

Collaborate with information 

security’s best and brightest. 

EXPAND YOUR OUTLOOK 

Attend world-class 

keynotes. 

HARNESS YOUR STRATEGIES 

Discover practical solutions 

to implement at the o�ce. 

THE reat Cipher 

Mi htier than the Sword 

Protect Your Kin dom. 

Learn How at RSA® Conference 

Re ister Now! 

www.rsaconference.com/bioit 

s av e 

$700 

Before Friday, 

November 

18, 2011 

©2012 EMC Corporation. All rights reserved. EMC, RSA, the RSA logo and the RSA Conference logo are registered trademarks of EMC Corporation in the United States and/or other countries. 

All other marks are trademarks of their respective companies. 

,

CONTENTS 


Tooling up for Smarter Studies 

Two industry studies found 

need for appropriate trial 

planning and tools. 

BY DEBORAH BORFITZ 

Separate industry surveys by information 

technology research and advisory firm 

Gartner and global software company 

ClearTrial make a strong case for clinical 

resource management tools in the costcutting 

arsenal of biopharmaceutical and 

medical device companies. 

The Gartner survey of industry sponsors 

and their technology partners late 

last year identified several clinical study 

best practices. 

For starters, study-related activities 

need to get appropriately planned upfront 

to the right level of depth and detail, says 

Gartner analyst Steven Lefebure. Companies 

don’t always devote sufficient time 

to planning, creating costly mid-study 

surprises. Project managers also need a 

firm understanding of the study schedule 

and required resources so that information 

can be used to better plan studies and 

keep them on track. 

Third, companies need to better 

match protocol design and study. Many 

protocols get “very ambitious” in terms of 

clinical measures and endpoints without 

an understanding of the downstream consequences, 

Lefebure says. “It’s essential to 

balance out cost and complexity with…the 

scientific factors.” 

Studies require technology-based support 

at every stage, from data capture to 

regulatory document management and 

submission, continues Lefebure. Productivity 

improvements and cost reductions 

have already been seen in this arena, but 

the technology itself has introduced issues. 

“We find seams between systems, 

handoff complications between EDC 

[electronic data capture] systems and 

data management tools at the sponsor 

organization, access problems, and…issues 

in terms of how medical information 

gets coded across a study.” The multitude 

of systems employed to do discrete study 


JIM NEWBERRY 

ClearTrial CEO Mike Soenen says the platform excels at planning, forecasting, and tracking. 

tasks only adds to the complexity. 

Study information with real-time visibility 

is yet another industry-identified 

best practice, says Lefebure, although this 

is still not the case at many organizations. 

As suggested by earlier Gartner research, 

cross-organizational information sharing 

by the sponsor and its clinical research 

organization (CRO) partners is another 

favored practice, especially since their 

operations and activities can be highly 

interwoven. Ideally, sponsors are collaboratively 

engaged with CRO partners in 

“honest and real communication about 

study status.” 

Finally, the industry-best planning 

process involves both the sponsor and 

its CRO partners in protocol design and 

budgeting. This gets all collaborating 

organizations “on the same page” at study 

launch, says Lefebure. 

Purpose-Built Tools Needed 

These best practices are “necessary but 

not sufficient” to improve study performance, 

says Lefebure. Also vital are clinical 

resource management tools “tailored 

to the job at hand” that can turn information 

into actionable insights. “Business 

intelligence tools are not enough.” 

EDC technology will “fade a bit into the 

background…because it’s not necessarily 

vital to achieving the next breakthrough 

in future operational efficiency. A lot of 

gains have already been achieved in that 

category.” 

Lefebure advises companies to seek 

out clinical resource management tools 

whose planning and budgeting features 

“reveal all assumptions” from protocol 

development through study execution. 

The software should allow a collaborative 

environment for transparent information 

sharing to get “more eyeballs” on problems, 

he adds. 

Linked study planning and execution 

tools will ensure study plans aren’t 

“obsolete” once trials get underway, 

Lefebure continues. Gaps between plan 

and practice can be immediately identified, 

along with needed actions to ensure 

the best possible outcomes in terms of 

resource use. 

Although industry opinion is mixed 

on whether or not systems integration 

helps with study execution, Gartner research 

indicates integrated systems and 

approaches more effectively “move the 

needle” on performance, Lefebure says. 

Industry is likewise split on the value of 

simulation and optimization tools. Software 

that enables what-if analysis and 

scenario planning, in Lefebure’s view, is 

“essential to the future” because it allows 

assumptions and plans to be tested before 

real resources are expended – notably, on 

costly protocol amendments once a study 

is underway. 

Lefebure further discusses Gartner 

research and industry best practices in 

a new video posted on the ClearTrial 

website.

ClearTrial’s Supportive Technology 

ClearTrial has the only fully integrated 

system for clinical planning, forecasting, 

outsourcing, and project and financial 

tracking, notes CEO Mike Soenen. The 

clinical study operational plan and detailed 

study budget also get built from the 

“bottom up” based on assumptions from 

clinical operations professionals. 

Multiple operational scenarios can 

be quickly developed based on timeline, 

cost, or resource objectives, says Soenen. 

Once a study is underway, heads of clinical 

development and operations can “easily 

view project status and trends,” and 

project managers can “quickly drill down 

to pinpoint underlying problems putting 

the study at risk.” New assumptions can 

be entered into the system “based on the 

problems identified to determine the best 

operational plan for getting the study 

back on track—in a matter of hours.” 

The technology also further supports 

the kind of strategic, long-range planning 

PAREXEL 

(continued from page 22) 

clusion/exclusion criteria for patients, etc. 

What about new and emerging eClinical 

technologies? 

The R&D focus has shifted more toward 

the convergence of the tools and providing 

a comprehensive eClinical suite, 

and somewhat less on new features and 

functionality. Of course, there is always 

development work going on, whether it’s 

for new medical imaging analyses or making 

sure we can support the latest imaging 

modalities. But I think the biggest trend 

has been investing in a platform that 

allows the various technologies to work 

seamlessly together. 

Another trend would be the ability 

to leverage other kinds of datasets like 

electronic health records (EHRs), which 

have the potential to be helpful in a number 

of ways including identifying eligible 

patients. With the right search criteria, 

a database could be analyzed in an anonymized 

way to determine if there is an 

attractive population at a given site for a 

study. I don’t think that the technology 

advocated by Lefebure 

In a separate survey of industry professionals 

with clinical study budget 

responsibilities, ClearTrial found the use 

of “old tools” and “wrong tools” hampering 

the efforts of life science companies 

to improve operational efficiency, says 

Soenen. Well over half of respondents rely 

on Excel as their primary tool for study 

budgeting. 

The same survey revealed serious 

operational inefficiencies. Only one in 

ten surveyed are able to keep their cost 

variances, from forecast to actual, at 5% 

or below. “What was surprising is that this 

pattern applies across the board, regardless 

of company size.” 

Among other disturbing survey 

findings: 

• 65% of respondents take five weeks or 

more to complete the review and revision 

cycle for a single study. 

• 62% of respondents require three weeks 

or more to roll up individual study bud- 

and data standards are ready to support 

the capture of all of the data needed for 

a clinical trial from an EHR in the near 

term. I do, however, believe that we are 

going to see more and more use of EHRs 

for safety surveillance, and probably to 

support some types of observational research 

in the future. 

That’s another one of the big trends 

we see—observational research... used 

to look for safety signals or to evaluate 

alternative treatments for purposes of 

comparative effectiveness. 

From a reimbursement/safety standpoint, 

REMS—risk, evaluation, mitigation 

strategies—that are mandated by the FDA 

are increasingly relying on non-interventional 

or observational research. Our late 

phase technologies are being used in these 

settings to enable more efficiency. 

What are among the biggest headaches 

or challenges for you? 

I don’t know if I would call it a challenge, 

but we must always be vigilant to ensure 

that we are executing on time and on 

budget to appropriate quality standards. 

One real challenge relates to the 

conduct of clinical development in some 

gets into a budget portfolio 

• 79% of respondents are only “somewhat 

confident” or “not confident” in their 

budget forecasts. 

• 88% of respondents have a typical budget 

variance of at least 6%, with more 

than half of this number experiencing a 

variance of 11% or more. 

At least some ClearTrial customers are 

having a decidedly difference experience, 

says Soenen. One top-20 sponsor using 

the software reports that annual cost 

variance is less than 1% across its clinical 

portfolio. 

A small biotech customer successfully 

negotiated cost savings of $2 million with 

its CRO for a single phase II oncology 

study. And a mid-size customer reduced 

its contract closure time from 2.5 months 

to 2.5 weeks for outsourced studies using 

ClearTrial as the common platform for 

negotiations with its CRO. “This proves 

that operational efficiency gains are indeed 

possible,” observes Soenen. • 

emerging markets. In some countries, 

one is entering markets where the investigators 

are less experienced and where 

you lack a pool of experienced talent. As 

an organization, to deliver reliably, we 

must take on an increased responsibility 

for training investigators, for training 

employees, and essentially building an 

industry where it did not exist before. 

In this regard, CROs like PAREXEL 

have worked with regulators and government 

officials and the industry to 

advance the adoption of ICH-GCP in 

emerging markets for biopharmaceutical 

development. 

Ultimately, you can be as good as the 

quality of the drugs that are going into 

man, right? 

Our job is to provide high-quality research. 

We hope our clients are successful, 

but our responsibility is to conduct clinical 

trials that are adherent to all of the 

applicable regulations. Our job is to make 

sure that we do good science. 

We believe that the CRO industry has 

an important role to play in innovating 

around how to conduct clinical research 

more effectively and efficiently. • 


CONTENTS

CONTENTS 


NuMedii’s New Way to ‘De-Risk’ 

Drug Repositioning Work 

Stanford University spin-off relies on database to identify new drug uses. 

BY DEBORAH BORFITZ 

A newly minted biotechnology company 

is offering to match the molecular genomic 

activity of previously approved medicines 

to that of known diseases to help 

drug makers find new uses for therapies. 

“We have two published studies demonstrating 

[our technology platform] can be 

used that way, and a third pending publication,” 

says Gini Deshpande, co-founder 

of Menlo Park, CA-based NuMedii. 

The company’s matchmaking capability, 

which has been likened to an “online 

dating service,” is driven by a strong computational 

engine that reduces the search 

for new indications for existing drugs, 

says Deshpande. The company is based 

on technology developed in the Stanford 

lab of Atul Butte, who is a co-founder of 

NuMedii (along with Joel Dudley). 

A multitude of other companies are 

trying to reposition approved drugs 

using more costly and time-consuming 

approaches, including cell based assays 

for screening an entire library of drugs, 

says Deshpande. NuMedii is less a fishing 

expedition than “educated fishing,” as 

one National Institutes of Health (NIH) 

scientist described it. 

What distinguishes NuMedii is an 

annotated and normalized database developed 

at Stanford that holds genomewide 

molecular profiles for more than 

300 diseases, as well as the informatics 

know-how to use it to identify new uses, 

including those still in clinical development, 

says Deshpande. It is also the first 

computational company to test its hypotheses 

in a pre-clinical animal model 

context and publish the results, which 

could help drug makers “de-risk” their 

medicine repurposing work. 

As reported in Science Translational 

Medicine, two predictions made by the 

technology—now licensed to NuMedii— 

have demonstrated preclinical activity 

in mouse studies (Dudley et al., 3:(96): 


96ra76 and Sirota et al., 3:(96): 96ra77 ). 

One of the predictions helped reposition a 

generic anticonvulsant medication for the 

possible treatment of inflammatory bowel 

disease. The other aimed a generic antiulcer 

drug at lung cancer. A third prediction, 

also for a gastrointestinal indication, 

will soon be written up in the literature. 

“The platform essentially marries the 

Stanford database with other drug, data, 

and knowledge bases,” says Deshpande. It 

can be tapped to find a disease whose molecular 

profile either counters or mimics 

that of a commercially available medicine. 

The NuMedii platform has potentially 

broad applications, she adds, but repositioning 

drugs with known safety profiles 

was the easiest starting point. 

Platform Efficiencies 

The timing couldn’t be better, given that 

the NIH has been actively pushing drug 

repositioning. Novartis, GSK, and Pfizer 

already have internal repositioning efforts. 

NuMedii’s approach would also be 

an efficient way for such companies to 

find first-ever treatments for a host of rare 

diseases, notes Deshpande. 

NuMedii is in the midst of establishing 

partnerships with several pharmaceutical 

companies to demonstrate the breadth 

of the platform and enhance its value, 

‘ The 

NuMedii platform 

essentially marries the 

Stanford database with 

other drug, data, and 

knowledge bases.” 

Gini Deshpande, NuMedii 

says Deshpande. She’s hopeful the methodology 

will get used early in the drug 

development process to help companies 

“maximize the potential” of approved 

compounds in development by testing 

them for additional, multiple indications 

in parallel. NuMedii’s platform could also 

be used to detect potential blockbuster 

indications for current, low-volume niche 

products, she adds. 

NuMedii faces more of an uphill battle 

in the clinical development realm, where 

computational technology is a novelty, 

says Deshpande. But the platform could 

prove valuable in guiding and prioritizing 

new drug development programs, together 

with physician input on real-world prescribing 

and dosing patterns. The technology 

can’t definitively predict a drug’s 

failure, given the volume of confounding 

factors (such as patient compliance), but 

it could capture its efficacy odds overall 

and in certain subsets of patients. 

Ultimately, the platform could be 

used to identify potential biomarkers of 

disease and genetic receptivity to certain 

drugs, says Deshpande. “Preliminary 

publications have shown that these disease 

genomic databases can also be used 

for biomarker discovery and we hope to 

pair this approach with drug indication 

discovery over the next year.” •


PerkinElmer 

Targets Holistic 

Data Solutions 

A series of acquisitions is expanding and refining the 

company’s focus, explains CSO Dan Marshak. 

With its recent acquisitions of CambridgeSoft and Geospiza to name but two, 

PerkinElmer is signaling a new strategy that highlights data analysis and software as 

much as its traditional strengths in hardware and chemical analysis. Spearheading 

the new strategy is Dan Marshak, an accomplished cell biologist who has served as 

PerkinElmer’s chief scientific officer for five years. 

Marshak spent a decade at Cold Spring Harbor Laboratory, studying cell cycle 

control in cancer before helping to set up one of the first stem cell companies, Osiris 

Therapeutics. “We went from two guys eating sushi to 117 employees raising over $100 

million,” says Marshak. At PerkinElmer, he reports to CEO/chairman Rob Friel and 

has a key role in formulating new technology strategies and acquisitions. He spent two 

years as general manager of operations in China—PerkinElmer is now one of the leading 

makers of hepatitis and HIV testing systems for high sensitivity testing in China. 

Marshak sat down with Bio•IT World chief editor Kevin Davies to discuss 

PerkinElmer’s evolving strategy from both business and scientific perspectives. 

Bio•IT World: PerkinElmer has made a 

number of interesting acquisitions lately. 

Why all the recent activity? 

Dan Marshak: We’ve been doing a lot of 

acquisitions and divestitures for the last 

10 years. We divested our fluid sciences 

business in 2006, and then last year the 

Illumination and Detection Systems 

(IDS) business, which was quite different 

than many of our other business-tobusiness 

health science-related products. 

We were able to take that cash and 

reinvest it in a number of different areas. 

We’ve decided to focus on human health 

and environmental health. Our legacy 

business in analytical chemistry is now 

focused on specific end markets, particularly 

in environmental laboratories and 

environmental testing—industries that 

need to have strong analytical chemistry 

to preserve the environment. We also are 

the leader in inorganic analysis—heavy 

metal analysis in water samples. We’ve 

been very active in food testing as well. 

Environmental health is about half our 

business, including instruments, reagents 

and software. 

About 25% of our business is in services—instrument 

repair or maintenance 

services, or validating for FDA purposes. 

Typically a scientist isn’t qualified to strip 

[an instrument] down, move it to another 

building or continent and reassemble it, 

get it tested and working and revalidate it. 

Your most recent acquisition is Caliper 

Life Sciences. What is the rationale for 

buying Caliper and how will it complement 

the existing technology portfolio? 

Caliper Life Science’s focus on next-gen 

sequencing workflow is an ideal fit with 

PerkinElmer’s NGS service as well as 

our Geospiza software. The LabChip is 

essential to ensuring the quality of the 

samples prior to sequencing. The combined 

offering will supply unmatched 

value in providing high-quality samples to 

the rapid speed required by sequencers as 

well as the informatics needed to analyze 

the massive amounts of data generated. 

The LabChip also allows the separation 

and purification of small quantities of 

biological contaminants within food and 

water testing… 

Caliper’s differentiated platforms for 

animal and tissue imaging will enable 

PerkinElmer to offer scientists in translational 

medicine the ability to understand 

at molecular, cellular, tissue and animal 

levels what a biomarker or drug target is 

doing. We are very excited about being 

able to offer our fluorescent biomarkers 

to Caliper’s IVIs customers. By combining 

Caliper’s and PerkinElmer’s expertise, 

researchers will be able to multiplex fluorescent 

and bioluminescent in the same 

experiment as well as at different times 

in the same animal to better understand 

disease mechanisms. 

Where is your focus in the human health 

side of the business? 

About two-thirds of that is diagnostics, 

one third is in the research products area, 

which supports both the pharmaceutical 

and biotech industries as well as academics 

funneling new discoveries into drug 


CONTENTS

CONTENTS 


discovery. 

In diagnostics, we manufacture some 

of the world’s fastest, highest contrast 

digital X-ray detectors. We’re one of the 

leaders in amorphous silica flat panel 

X-ray detectors, sold for medical purposes 

to GE. In oncology, we make very 

fast detectors that are used in therapeutic 

oncology devices… We recently acquired 

Dexela, a UK company that does CMOS 

X-ray detection. So we do both CMOS 

and our classic amorphous silica X-ray 

detectors in diagnostics. 

The central part of our diagnostics 

business is around pregnancy and birth— 

newborn screening, cord blood banking, 

prenatal/maternal health. We’re a leader 

in prenatal testing for Down’s syndrome 

and other disorders. Probably 80% of 

all the newborn Guthrie heel-stick blood 

spot cards are done through PerkinElmer 

systems. We recently acquired a company 

that produces these filter cards, all the 

way to the puncher and the instruments 

to do multiple testing of different types 

of analytes. Some of our most advanced 

areas are in the software for doing statistical 

analysis of the data. It’s easy to 

measure something and produce a number. 

What’s difficult is to know whether 

that number is significant, so a physician 

can say whether a child has a disorder or 

needs further testing. 

On the DNA side, we acquired Signature 

Genomics, which has proprietary 

content on Roche NimbleGen array kits. 

They do a service of prenatal and newborn 

arrays for further diagnosis of genetic 

disorders. They have a database they 

provide through unique software for genetic 

disorders called Genoglyphics. This 

year, we launched the first foray into using 

those chips in oncology for hematological 

malignancies, called Oncoglyphics… 

We’ve expanded our diagnostics 

through acquisition of SYM-BIO Life Sciences 

two years ago in China. SYM-BIO 

is a leader in the high sensitivity test for 

hepatitis, HIV, and some STDs. There are 

100 million carriers of Hep-B in China. 

We’ve been able to fill that niche and we’re 

expanding that business significantly. 

What is the over-arching goal or strategy 

to these acquisitions? 

Up to the 1970s, PerkinElmer was the 


leader in introducing new instruments— 

we introduced the first infrared spectrometer, 

the first GC mass spec, a lot of firsts 

in analytical chemistry. In those days, the 

learning curve, the technology curve was 

very much in the hardware. The field has 

matured in the last 30 years and a lot of 

companies have entered the field. Ours 

is still outstanding technology, but the 

differentiator for the customer is not as 

much in the box as in other parts. 

Also, the users have changed... [Customers] 

need help on sample preparation 

and getting it to the instrument; on 

the other side, it’s about understanding 

the data coming out, turning that data 

into information and then using other 

resources to turn the information into 

knowledge. They want the complete 

solution from one vendor: so samples, 

instrument, reagents, consumables, and 

the software, and the analysis, and training 

and service support from one source. 

We’re trying to provide that. 

So it’s about providing a more holistic 

data to knowledge solution? 

Moving from data acquisition to knowledge 

is not trivial and it’s not simply 

laboratory information management. It’s 

really using the new tools of the Web 3.0 

and cloud-based tools to understand what 

else is out there to collaborate or interact 

within or outside the facility. 

Some of the software no longer needs 

to be tied to the instrument. It’s really 

software-as-a-service in some cases— 

software that enables the customer to 

take their information and turn it into 

solutions. 

Some years ago, we bought Evotec 

Technologies, which had cell-based 

screening for high content screening. The 

accompanying software actually runs 

on its own—it’s very useful for sample 

analysis and image analysis either from 

our instrument or from open sources, and 

in general for analyzing cellular imaging. 

Our high-end instrument is called Opera, 

and there’s a lower-end instrument called 

Operetta. 

The software (with a graphical user 

interface) is called Harmony, but the central 

software that’s used for analyzing the 

data and moving to a knowledge-based 

architecture is called Acapella—because 

it is without an instrument! We’ve now 

launched Acapella on our Columbus Conductor 

Workstation, which allows you to 

analyze image files and understand what 

is going on to build models… 

CambridgeSoft is the leader in electronic 

lab notebooks, enterprise wide 

but also for the individual researcher. 

They also have ChemDraw and other 

applications on that platform… There 

are tools linked to instruments but there 

are also tools that scientists will use independently 

and then these systems like 

electronic lab notebooks (ELNs) or workstations 

that pull data together and allow 

knowledge creation. That goes along with 

Signature Genomics and the Genoglyphics 

and Oncoglyphics software. Whether 

we do the service, use our array chips or 

our Luminex system, or clinical sequencing, 

we’re still developing an information 

and knowledge solution for the customer 

using the software. 

How will this help researchers 

down the road? 

We’d like the researcher of the future to be 

able to sit at a terminal or on an iPad and 

access all these things, and understand 

better what (s)he needs to do next, to call 

on service support or collaborators as 

needed, to reorder reagents and consumables 

as needed, to reserve data for FDA 

purposes and make sure things stay in 

the right place. It’s more than laboratory 

information management—it is knowledge 

creation and solving problems for 

customers. 

There are some very highly data intensive 

systems now. Mass spectrometry, 

imaging and DNA sequencing generate 

very large bodies of data. So you do the 

experiment quickly and then you spend 

your time analyzing. This has happened 

in physics, too. There is the ability to 

analyze that data more quickly in very 

large data sets. We have customers with 

petabyte storage devices because they 

have so much data. Even our Conductor 

workstation is sold with 24 terabyte 

storage. So being able to manipulate 

large data sets, and share them with your 

collaborators in Europe or China, maintaining 

security, and to manipulate the 

information to garner the desired results, 

is very important.

What does the acquisition of Geospiza 

say about your interest in next-gen 

sequencing? 

Our DNA strategy is still a work in 

progress. I mentioned Signature Genomics 

for array analysis and Luminex 

as a platform to develop bead-based assays. 

This year we acquired Chemagen 

Biopolymer Technologies in Germany, 

which is a magnetic bead-based nucleic 

acids purification system, and competes 

with the likes of Qiagen on methods for 

isolating DNA. 

Downstream, the Geospiza deal was 

terrific for us because they had some of 

the best technology for DNA sequence 

analysis and managing sequence information. 

We’ve set up a DNA sequencing 

service. Our goal was not to enter the 

field of DNA sequencing technology per 

se. We’re providing sequencing services 

at a very high level of automation, accuracy, 

service and security, as well as the 

Geospiza software for analysis. There are 

still some gaps from sample acquisition 

and processing all the way down through 

analysis of the results. We hope to fill 

those gaps and have a more complete 

DNA strategy, both in the service and 

product offering. 

Why did you decide to get into the 

sequencing service business? 

We heard from a lot of customers that 

there was a demand, both in pharma and 

in academia. One of the leading providers 

of these services is BGI in China, but we 

heard a lot of interest in finding a domestic 

supplier of high quality services, and 

we thought there was an opportunity for 

us to enter this market. 

We typically use Illumina instruments, 

but we are methodology agnostic and 

will go where the field needs in terms of 

technology. We want to provide—from 

sample to knowledge—that complete 

continuum to the customer to try and 

solve their problems, and allow them to 

back away from having to be experts in 

every technology. 

Dick Begley, previously the president 

of 454 and at Agilent before that, is run- 

ning the business. We’re trying to provide 

very high quality service, very good data 

capabilities, but we’re starting slowly. 

Rome wasn’t built in a day and neither is 

our DNA sequencing. 

Are you planning more 

acquisitions? 

Well, a) you’re never done and, b) we still 

have plenty of money and debt capacity 

to do more investment. So no, we’re 

not done! We’re still very interested in 

acquisitions of significant size that may 

be somewhat transformational but we 

continue to consider ‘bolt-ons’ for the 

existing businesses. 

Some of the areas of overlap between 

human health and environmental health 

include things like pathogen detection, 

not only for infectious disease but also 

in food and water. So you can see where 

technology is sort of agnostic to what you 

use it for, and we could use nucleic acid 

testing technology as well as immunoassay, 

imaging and other things to help us 

cross that frontier. • 

Final Print Issue of Bio-IT World 

Starting in January 2012, Bio-IT World will publish 

exclusively as a more frequent, digital magazine. 

Print subscribers will automatically receive the 

digital edition beginning in 

January. 

Earlier this year, 

we launched a 

free iPad/iPhone 

app that not only 

shows off the printed content but 

also features video and other 

enhancements that will only grow 

in 2012. If you haven’t checked 

out our digital magazine, go to: 

http://bit.ly/bioitnew 


Up First Contents Front Base The News [09–10•11] Bush Doctrine 


of This Issue 

CLICK HERE! 

Special Report 

The latter requires a different level of database information, come In an in that effort case to create is by no stigmergy means guaranteed. in this space, DSEC has 

NGS in Interpreting this case transcription and the factor Personalized binding Genome motifs. As these implemented Our cover image Medicine: 

a new tool—a depicts virtual Chris Toumazou, poster gallery the that founder enables and 

Stigmergy, 

elements Interpreting 

Jackson Lab Priorities 

rarely act on their own, their integration into a scientists CEO of a relatively and startup small companies British company, to presentDNA summaries Electronics, of their 

network 

19 Seize 

or 

the 

pathway 

New: 

system 

Laying 

is 

the 

a reasonable 

Clinical Genomics 

subsequent 

Pipeline in Wisconsin 

new which technologies has been licensing in a virtual its intellectual exhibit on the property DSECto website some of the 

Computational analytics key in push to more 

move. 24 The Richard And finally, Resnick’s Role all these Quest findings for of should Genome Data be Governance 

presented in Interpretation 

biggest translational names in the business, research. 

(http://www.chicorporate.com/dsec_poster_list.aspx). 

including Ion Torrent Systems 

Anyone? 

an the intuitive visualization Genome 

environment, allowing researchers and SoRoche. far, more Toumazou than 60has posters a distinguished have been uploaded record in to medical the site, 

to 

27 

interactively 

DNA Electronics 

combine 

is 

experimental 

Powering Preventative 

results with other 

Medicine 

data which devices, are and presented his latest ingizmo, four categories: the ‘SNP-Dr,’ Cardiovascular which instantly Toxicity, calls 

BY KEVIN DAVIES 

and to see the result in an understandable format. Deep, Discovery to mind Mr Pharmacology, Spock’s tricorder, Genetic bracing shows Toxicity the winters potential and Hepatic of of Maine, real-time ToxicLiu 

31 The Bedrock of BGI: Huanming Yang 

have one big job left before they put 

ity. genomic It is free diagnostics to upload(page and display 27). has no theillusions posters and of the available challenges to 

extensive, high quality data content is therefore a critical 

The advance of Next Generation Sequencing technology has 

component 

35 An NGS 

of 

Analysis 

each of these 

Software 

steps 

Smorgasbord 

Several articles look at new software initiatives from the 

KEVIN me out DAVIES to pasture. Singapore needs 

anyone who would like to share ahead. theirFor poster all of with Singapore’s the DSECmuch 

and is required to enable 

enabled researchers to generate genome wide sequencing 

new ERNIE a refresh, 

biological BUSH and perhaps I do as well.” 

community. commercial Our and academic hope is that fields. providing publicized Managing this funding opportunity editor problems, Allison forProf 

Liu 

‘I 40 Kevin So welve McKernan says months insights. 

Edison ago, Leaves Liu, we arguably published Life Technologies a special issue on 

data of a High 

of unprecedented fitt stigmergy interviewed will 

Open 

quality stimulate many source leading tools 

and others quantity. notes 

like genome not 

CIRCOS 

only that Chromatin informatics to the 

(used 

upload NIH 

to 

IP budget other companies visualize 

posters is flat. 

the 

structural variants here) can easily be incorporated 

(ChIP-Seq), Genotyping (DNA-Seq) and expression analysis 

Turning 

44 most Galaxy tigmergy prominent Bio•IT World 

Results 

Provides is currently medical dedicated 

into 

Life defined researcher to “The 

Medical 

Support in Wikipedia Road to the 

for 

Action 

NGS Exploration 

as: $1,000 for buttheir also to latest investigate tools and and trends, evaluate “The including U.S. the new situation Knome, technologies isReal not Time rosy being ei- 

in Singapore Genome.” and theWhile two-term we didn’t president expect to reach that mo- Genomics, 

With lowered sequencing costs, the introduction of 

(RNA-Seq) 

exhibited. 

due Partek, to our and adaptable DNASTAR 

are three of the many application 

ther,” 

system (page he 

areas 

says. 

architecture. 35). On the open- 

currently 

of 46 the BGI Human “A Launches mentous mechanism Genome if somewhat New of indirect Organization Big arbitrary Data coordination Journal: threshold between GigaScience 

so soon, source To further front, we enhance meet the thetwo interest founders What in this appeals of virtual Galaxy, toposter Liu an increas- about exhibit, JAX 

benchtop sequencers, and the emergence of multiple 

used for research purposes. Epigenomics, transcriptomics 

(HUGO), agents there’s who is or no returning actions. doubt The we’re to the principle getting Unitedvery 

is that close. the trace This past left ingly the DSEC popular organization platform for haseasy implemented is and thatefficient the institute what access might “has to a bea variety called degree 

strategies T for data analysis, the medical application 

and 

of NGS 

the analysis of structural variants are also widely 

States 48 VAAST after in summer, the a decade Potential environment Illumina abroad for to by announced Genome become an action theyet 

Analysis stimulates another Software the drop per- in its of iterative genome stigmergy informatics (i.e. tools an act (page of freedom stigmergy 44). inintended terms oftoorganiza pro- 

S technologies personal new is a natural next step. However, if medical 

used with this technology. With data generation growing 

51 president De formance Facto genome and Software sequencing of CEO a next ofaction, The Standards service, Jackson by dropping the same in Next-Gen or the a introduc- different Genologics mote On another page 24, act Richard of stigmergy) Resnick, tion byCEO holding andof capabilities GenomeQuest, quarterly innovation thatdis I just 

action tory Laboratory agent. individual is In to (JAX) that be price based way, in Bar below subsequent on Harbor, $10,000. scientific Maine. actions For results, academic tend several to reinforce and issues pharma at an exponential cusses awardshis competitions. rate, company’s the need ambitions Infor this efficient competition, don’t in the see analyses genome in four anyand analysis other recently university realm. upload- 

need 

customers 52 Liu and NGS to will build be Software seeking take addressed: 

on up each whole his other, Systems new genome leading post in for sequencing Janu- to the the spontaneous Enterprise services, emer- the comprehensible cost As ed posters one visualizations might areexpect nominated of has someone by become the department. chairman who critical. took his of I saw the bioinformatics 

DSEC a veryAdvi robust 31 

Use paired-end 

per 

n 

ary 

Sequencing 

gence genome 2012, RNA-Seq of succeeding coherent, is now 

platforms experiments 

as apparently Rick low as Woychik, $4,000, 

must to systematic identify provide 

who competition 

data 

activity. being 

that 

Stigdriven 

training 

is both 

sory Board from as top Broad examples Institute oforganization director new technology Eric Lander, that innovation had Resnick sufficient and is 

gene fusions 

by is now the mergy and 

emergence deputy is read-throughs 

a form director of of many self-organization. ofnew theservice National providers, It produces and complex, even Turning one a Data knowledgeable into Results and refreshingly resources candid the because spokesperson DSEC of members excellent for the 

reliable and reproducible. 

or Institute two seemingly sequencing of Environmental intelligent service structures, brokers, Health such without Scias 

Denmark’s need for any Blue- Analysis generally genome informatics starts with industry. the alignment management of reads are asked ofto mouse a to vote services. on 

n SEQ, Analysis pipelines must also be reliable and reproducible. 

Up Front offering to find the right sequence and analysis 

Edison Liu 

ences planning, in Research control, Triangle or even Park, direct N.C. communication Liu 

between partner reference genome IT/Workflow and the subsequent They analysis understand one of variations of these thatas there theirare fa- 

for is the Additionally, the a client’s founding agents. needs. As executive they such it will supports director have to efficient of be the standardized collaboration enome, the and 

8 compared dynamic portions Challenges 

to this reference overand time Opportunities 

(e.g. potential challenges vorite ahead new technology in terms of 

Genome certified. As between Ed the Liu Institute cost extremely on of whole-genome Singapore ofsimple Singapore agents, Science sequencing (GIS), who and lack halves and any different memory, every five 53 Sequencing the Earth: the Computational 

SNPs, 

conditions.” Speaking of candid, I was 

re-arrangements). The next 

what struck the mouse by the open model poster attitude can for that do, of and quarter. BGI they 

n months which Medically intelligence Jackson has or grown so, relevant the or Lab to even focus 27 Priorities individual laboratory disease inevitably databases awareness groups shifts to the of need cost each Liuto of suggests other… analyzing be that institutions founder Burden Huanming that Find are out and which Yang, Future need key who toplayers be Role gave medically us of in an gene FPGAs For exclusive relevant.” Q2 networks 2011, interview the or winpath- steps are then application-specific, 

and andintegrated interpreting with the existing genome. data The task content of analyzing and their the biologically flood 

ways are associated with your NGS data and how 

9 Stigmergy nearly Patent 300 was Reform’s staff. first Liu observed is ‘Brave credited in New social withWorld’ 

insects, not however divided into it departments, during a visit like to JAX, Boston earlier The future this year of the (page ner mouse was 31). VivaQuant’s disease Yang has model 

of next-generation an example being a copy number 

being relevant is not a driving restricted counterparts. 

force to sequencing in eusocial the creation creatures, (NGS) of the data or even is have likened to physical a better by the chance of worked they influence molecular mechanisms. 

10 analysis or the In doing 

identification Every wonders, a deepIssue inbuilding 

is a BGI critical into issue the world’s poster, for JAX. largest A Novel “By using genome Alin- Broad Biopolis 

of areas 

If systems. these AstraZeneca Institute’s research and On the other Matthew center Internet Opens as (see, yet Trunnell there Predictive unforeseen “Building are to many driving Science collective requirements 

tegration. in a snowstorm. proj- “Historically, sequencing computational center, providing formatics services and the for gorithm a sequence large number foras Highly a linkage of 

of higher and/or First lower Base read BY density. KEVIN DAVIES 

are “If Buzz we ects met, Center in just where Singapore,” NGS waited users in has Russia for interact the Bio•IT the potential roads only World, to by be to modifying June ploughed, become biology local it a would significant parts is split be among academic 3 to 4 different and pharma between clients. But mouse as in and any Automated human, arena, reaching Measure- we can the put 

Yet, these and other first steps are 

technology really 2008). of their easy, shared but in we the virtual have enablement to environment. white-knuckle of personalized Wikipedia it now,” departments. rather is medicine. an than It’s not pinnacle common 5 Interpreting is they one thing, get staying the valueGenome added there is inquite thement medical another, of QTtranslational and Interval. Yang 

wait 12 however Quebec’s long Genizon for the perfect Biosciences platform, Closes with negligible its Doors simply er- data does conversions not sugarcoat that BGI’s reduce challenges Genomatix in the next is the few proud years. 

Genomatix Liu example listsof three this.” offers primary comprehensive, goals as heintegrated, 

aggregated and into flexible a powerful unit. Around piece,” he says. As gene Our congratulations 

knockouts become 

The Russell Transcript BY JOHN winner RUSSELL of Illumina’s 2011 

rors, takeslong read lengths, and high throughput. Perhaps seeking the massive amount One of the of first raw NGS data platforms featured in Bio•IT World was 

turnkey 13 Reevaluating up his new post. 

solutions and the First, 

services Role “to move of for the into 

the entire Research the world, where computational biology ubiquitous, Liu wants to VivQuant to refocus andon to “in- all 

spectrum 58 CDER Must Have Clinical iDEA Trial Challenge Reform award 

inspiration human Openrelevance—translational Virtual from Collaboration a well-known is ‘next-generation’ research, another example, has linked expert, where up, to the aa 

it(usually is in institutions in still 2007, huge) when like number Kevin the McKernan novation of technologies.” took for the us “Most the through nominees. 

Creative Thethe mouse basics isof still 

of NGS Librarian data analysis in Pharma with a R&D 

Broad’s upstream NGS pipeline 

strong 

is humorously 

focus on 

named 

medical 

Picard, 

Easily overlay 

you company can 

multiple 

use posts other 

results 

a problem terms. 

from 

That’s on 

your 

the 

NGS 

the Webkey.” experi- 

and rewards Broad, those Sanger, regions who even or SOLiD Washington positions that may be 

Visualization” in the 

application. From first level alignment to variant calling to 

6 Company sequencing, Uni- now and thepart best Advertiser of mammalian Life Technologies. Index If model you have McKernan for acomplex poster 

which “Commercial” category. 

ments with 

Second, contribute 

our The feeds 

first 

isBush to ainto class 

solution, engage Doctrine a disease-specific pipeline appropriately 

genome 

genomics and 

annotation 

this isinoften a cost- 

to 

held upversity’s as a successful genome relevant center, to spent the not biological his within final 12 the question months physiology at Life Technologies and biology, that you leading he would says. the like R&D to 

the dubbed integration of multiple result files, we provide biological 7 On Deck 

understand 

effective commercial 14 biological Stigmergy, Firehose. manner application Agility 

contexts. 

toAnyone? increase of is stigmergy. at the a institute’s premium, So are says there department Trunnell, other but team of newly acquired Ion Torrent Systems, before stepping 

at practi- ofhand. computer While science.” this data conversion Liuis wants demanding to “highlight share in terms withthe the relevance mem- 

knowledge NGS impact. cal applications is still Third, posing and to ofmedically “conceptualize stigmergy tough questions relevant in pharmaceutical how for results we the IT from crowd R&D? your five NGS years down 54 this New summer. Products His ofnew theventure, mouse Medicinal in Genomics, has 

of processing power and storage requirements, 

bership systems 

it can be 

ofor DSEC problems (to 

data. later. canThe make The “It’s Our Drug Skeptical new the extensive Safety mouse to us,” Outsider Executive even says high-quality Trunnell. moreCouncil relevant.” background “We’re (DSEC, not The www.drugsafe- 

high-energy data Maine and Event sequenced 

automated and 56 pipelined Educational and released where 

for high-throughput Opportunities 

data from therethe are cannabis stigmergise?), not other genome. organisms you This can 

analyses. 

award-winning physics!” tycouncil.org) 15 A Big major Pharma’s priority was visualization established will Last be what Refuge: in tools Liu 2007 greatly calls Ma to promote Meds? enhance Liu says collabora- that the as ability much as may sound like some fancy new recreational visitgenomics the DSECstart website 

Turning Leaf 

he 

the cutter 

loves 

data ants 

GIS, 

into demonstrate 

he available.” 

meaningful the results, princi- 

And he wants to use synthetic 

however, 

to computational tiongain In inour developing meaningful 2011 genome analytics. pharma insight informatics R&D “The into safety very linkage special complex assessment issue, never biological we practices. intended offer a to stayples up, more but of indirect than as McKernan 

Inside the Box 

requires an interpretive 

Get about coordination: 

step 

a comprehensive 

explains biology stigmergy. (page to 

and a significant 

expression study 40), the or the contact effects 

amount 

overview 

goal is of my to 

of 

with mutations better colall 

processes. 

collection between (Ed Note: human DSEC of features, is and a sister profiles, mouse organization inand a trans- interviews to Bio•IT 10-12 around World.) years. the It lat- The initial understand approach 

16 Virtualization and the Cloud 

known 

the from potent 

plus in novel 

anti-cancer different transcripts genetic properties 

and league backgrounds. splice 

of Brian some 

variants. Murphy, of “We the can 

estlational is atrends virtual world in community NGS willand generally genome of morebethan informatics. through 2,000 pharma Perhaps JAX came company the high out most of quality the plant’s head blue. background of “When active business compounds. they information development de-convolute NGS at for several Cambridge complexity Data different Healthtech in an organismal As- 

gratifying genetics, employeesstory in genome interpretation this year is the levels. work For example, Our digital to annotate edition carries regions two of bonus relevance, articles a in this report: 

Insights genomics thatOutlook sponsors andseveral computational consortia. Their first contacted collective me, I thought sociates they at bmurphy@chacorporate.com. 

had the manner,” he says. “I’d love to explore that.” 

of analytics. missions Elizabeth Worthey and colleagues at the Medical College 

17 Single are I hesitate to Molecule improve to call the Sequencing economics it computaand 

and effectiveness wrong the Future person! comprehensive of I’m not a mouse story Finally, genome about geneticist, if you VAAST annotation have Interpretation 

(page seen other 48), database a examples promising must ofalgorithm stigmergy be for in the 

of tional safety Wisconsin evaluation biology—that (page (especially 19). often Worthey, means in thewhom areas someof 

I had discovery but the Contact that’s pleasure toxicology USA: not available the of issue. to detection pharma They allow want correlations R&D, of some- pathogenic we would with Push Contact mutations very multiple Pull much Germany: amidst like types to hear an of ocean genomic about of them. exome 

interviewing thing and 

Genomatix Software Inc. 

Genomatix Software GmbH 

10 non-clinical Briefs else—but this the development). summer concept in Copenhagen, of One analytics of DSEC’s played one primary toa pivotal takegoals 3025 Boardwalk, elements them role into 

Suite such or Send genomics, whole-genome me 

160 as transcripts, a note human pointing data, transcription There which out or has is 

Bayerstr. Survey 

demonstrating available been 

85a start much to sites academic attention your and/ examples users to the 

in engages is to the promote much IT, publicized informatics, the introduction, case computational 

of Nicholas qualification, Volker, genetics anda sick Wiscon- 

Ann implementa- 

Arbor, andor MI translational regulatory now 

48108 andmedicine. regions Iand will will report (promoters/enhancers). be They part on them of state a commercial package 

80335 inof future Munich scientific columns. Drilling affairs in by deeper Singapore, San Fran- but 

sin biology, tionboy of new whose simulations—the technologies genome was that whole sequenced improve gamut. the (almost prediction needed Complete the survey for a 


USA as a last to offill resort), clinical into a cancer the biology, center cisco-based May director’s one the stigmergy can 

Omicia pothen 

shortly. be assess despite Germany with And you! the what we 

function 

talk Liuto calls Laurie 

of “naivety these 

Goodman, among 

resulting That’s adverse www.genomatix.com 

what events in you’ll a positive before needthe diagnosis to make initiation all and aspects of therapy. humansition The studies Phone Volker and +1-877-436-6628 

thus they case the editorial director chance of Phone GigaScience, to +49-89-599-766-0 

win an a new Amazon peer-reviewed Kindle. 

Fax +1-734-622-0477 elements, 

dewant 

globalization. 

e.g. proteins 

I was 

encoded 

bureaucrats 

Fax by +49-89-599-766-55 

a specific 

in dealing 

transcript 

with scientists,” 

highlights of creasing 18 genomics Trials the the at failure work—not vast the potential rate Point-of-Care 

of just drugs of sequencing clinical in clinical genome trials onesequencing, due person to unex- that fit the open-access Ernie entireBush bill.” is journal VP and published scientific the situation director by See BGI, inpage Singapore devoted of Cambridge 37 to is big still Health data pretty in 

E-Mail sales@genomatix.com 

variant or transcription factor patterns E-Mail info@genomatix.com 

in a regulatory region. 

even the pected genome, though—as safetybut findings. the Worthey transcriptome, readily admits—the epig- gratifying Trading inout the Singapore genomics Associates. heat and He forcan life thesciences 

be reached (page at: ebush@chacorporate.com. 

46). (continued on page 11) 

CONTENTS 

Ed Liu on Singapore Science and 

BART NAGEL/FILE 

BANDWAGONMAN AT EN.WIKIPEDIA 

[4] [14] [8] BIO•IT WORLD SEPTEMBER | | OCTOBER | OCTOBER 2011 www.bio-itworld.com 

www.bio-itworld.com SEPTEMBER Cover photo-illustration | OCTOBER 2011 BIO•IT by William WORLD Duke [ 5 ] 

CONTENTS 


CONTENTS

CONTENTS 

Computational [GUEST COMMENTARY Biology 

] 

What Should We Call ‘Systems Biology’? 

Systems biology has been around for years. Is it time for a makeover? 

BY DESMOND SMITH 

Systems biology lies at the very heart of 

modern biomedical research and a number 

of review articles and conferences 

have caught the spirit of this movement. 

The discipline encompasses an assortment 

of related but distinct concepts, 

including the idea that detailed and 

comprehensive data from living systems 

will enable robust prediction of their 

trajectory and also the paradoxical notion 

that some biological behaviors occur 

in a relatively surprising and unexpected 

fashion, so-called emergent properties. 

However, the ideas underlying systems 

biology are not new. First articulated by a 

number of researchers in the 1960s, some 

of the principal notions 

were also articulated 

by Francis Crick in a visionary 

Nature review 

article in 1970 that anticipated 

the state of 

molecular biology in 

the year 2000. In his 

article (Nature 228, 

613-615 (Nov 1970)), 

Crick stated that “problems 

involving complex 

interactions can hardly 

be avoided… a simple 

example would be the 

3000 

2500 

2000 

1500 

1000 

500 

‘total’ behavior of a microorganism such 

as Escherichia coli, including all of its 

regulatory mechanisms.” 

More recently, the systems biology 

agenda has been resurrected by Leroy 

Hood with his founding of the Institute 

for Systems Biology in Seattle (see “All 

Systems Go at ISB,” Bio·IT World, June 

2002). This signal event has been followed 

by a growing body of work from the 

institute as well as several other groups. 

The renaissance of systems biology 

has depended upon the dramatic advent 

of new and interrelated genetic and genomic 

technologies that gather biological 

data with ever increasing speed. The 

midwives of systems biology are thus 

the accompanying “omics” technologies, 

0 


such as transcriptomics, proteomics and 

interactomics. At first, the large amount 

of data obtained by these omics technologies 

was impressive in its own right. 

More recently, however, there has been a 

tangible sense that mindless accumulation 

of data is insufficient, and that new 

insights are required if the discipline is to 

thrive. This disquiet has been exemplified 

by criticisms likening systems biology to a 

Stalinist five-year plan that will ultimately 

fall flat on its face. 

Personally, I am not so sure and would 

like to throw back at the critics a quotation 

attributed to the Generalissimo: 

“Quantity has a quality all its own.” 

Nevertheless, it does seem that the 

2000 ’01 ’02 ’03 ’04 ’05 ’06 ’07 ’08 ’09 ’10 2011* 

*projected total 

“Systems biology” references in PubMed jumped from 8 articles 

in 2000 to 2,422 in 2010, but 2011 appears to be leveling off. 

term systems biology is (already) becoming 

a bit tired despite the importance 

of the subject matter. The half-life of 

excitement for new disciplines does seem 

to get shorter with each passing year. 

After all, molecular biology was a good 

enough term for a topic that thrived for 

a couple of decades at least, while the 

term functional genomics seems like a 

distant memory, even though only a few 

years old. 

Bring on the New 

So, what would be a fresh and evocative 

new term for systems biology? The 

difficulty of developing an acceptable 

name reflects the broad landscape of this 

discipline. One recent suggestion from 

Eric Schadt is multiscale biology, referring 

to the diverse nature of the data used 

to construct models in systems biology. 

(Schadt is the new director of an institute 

dedicated to genomics and multiscale biology 

at Mt Sinai School of Medicine; see, 

“Partnering on Multiscale Biology,” Bio•IT 

World, July 2011) 

However, a few other alternatives do 

present themselves. 

• Biosignal processing is an attractive 

possibility. This name forges an analogy 

between the concepts underlying 

systems biology and electronic signal 

processing, except that the signals are 

biological (transcripts, proteins, nerve 

impulses etc.) instead of electrical. 

• Biowireomics would emphasize the 

notion of integrating biological wiring 

diagrams from many diverse domains. 

• In the same vein, bitomics emphasizes 

the now commonplace observation that 

biology is an information science. 

• Another possibility is Tukomics, in 

honor of John Tukey, coiner of the term 

“bit,” while Shannomics would honor 

the father of information theory, Claude 

Shannon. 

• Other instances that share the same sentiment 

are dataomics (because systems 

biology is concerned with integrating 

all relevant data types), totalomics 

(same sentiment) and kitchensinkomics 

(same sentiment, tongue-in-cheek). 

And of course, understandomics, 

because surely that is the final goal of 

systems biology. 

But other fields are also overdue for 

a name modification. One instance that 

immediately springs to mind is nanotechnology. 

However, those scientists with 

young children know that finding affordable, 

scalable childcare represents a much 

more fundamental challenge for modern 

biomedical research. 

“Nannytechnology” anyone? 

Desmond J. Smith is a professor in the Dept. 

Molecular and Medical Pharmacology at 

UCLA. Email: DSmith@mednet.ucla.edu



Eliminating Cost As a Factor 

Headline Please Xxxxxxx xxx Xxxxxxxxxx 

In Xxxxxxxxxx Applying NGS Xxxxxxxxxxxxxxxxxxx 

Analytics to Medicine 

Appistry’s ® Ayrris / BIO is making NGS analytics clinically actionable and cost-effective 

As we near the close of 2011, the 

applications for Next Generation 

Sequencing have never been as 

mainstream as they are now. Over the 

past year, we have continued to witness 

the evolution of this capability and its 

associated methodologies—from a mere 

set of disparate research projects to a 

clinically actionable set of solutions that 

can readily help fight real world diseases. 

Appistry, developer of the open, scalable 

Ayrris TM As we near the close of 2011, the 

applications for Next Generation 

Sequencing have never been as 

mainstream as they are now. Over the 

past year, we have continued to witness 

the evolution of this capability and its 

associated methodologies—from a mere 

set of disparate research projects to a 

clinically actionable set of solutions that 

can readily help fight real world diseases. 

Appistry, developer of the open, scalable 

Ayrris /BIO technology for advanced 

data management in genomic analysis, 

exists at the fulcrum of this powerful 

evolution—building the applications that 

make the promise of NGS a reality across 

our healthcare ecosystem. After all, the 

core value of NGS will not be realized until 

it is utilized not just in extreme disease 

management situations like critical care, 

but also within the entire lifecycle of a 

patient and integrated completely into 

our medical systems. 

So where do we stand now? Previously, 

NGS’s potential permeated only 

throughout research, but it is now turning 

the corner and rapidly moving into the 

clinical space. One example is prenatal 

scans, which will begin in earnest across 

thousands of newborns in 2015. This 

data will provide a genetic roadmap for 

all stages of life. 

While this application of NGS provides 

invaluable patient data, the data 

is complex—exponentially increasing a 

hospital’s data management and analytic 

burden. It also requires significant 

standardization, commoditization and 

automation of NGS analytics as applied 

to medicine. 

Unfortunately, with multiple sequences, 

multiple analyses and a holistic 

perspective of the applicability of genomics 

into medicine now on tap, the technologies 

currently available in the clinics 

TM The applications for Next Generation 

Sequencing have never been 

as mainstream as they are now. 

We have continued to witness the evolution 

of this capability and its associated methodologies—from 

a mere set of disparate 

research projects to a clinically actionable 

set of solutions that can readily help fight 

real-world /BIO diseases. technology Appistry, for developer advanced of 

the data open, management scalable Ayrris in genomic / BIO technology analysis, 

for advanced data management in genomic 

analysis, exists at the fulcrum of this powerful 

evolution—building the applications that 


the healthcare ecosystem. After all, the core 

value exists of at NGS the will fulcrum not be realized of this until powerful it is 

utilized 

evolution—building 

not just in extreme 

the applications 

disease manage- 

that 


ment situations like critical care, but inte- 

our healthcare ecosystem. After all, the 

grated completely into our medical systems 

core value of NGS will not be realized until 

within it is utilized the entire not lifecycle just in of extreme a patient. disease 

management situations like critical care, 

Where but also do within we stand the entire now? lifecycle of a 

Previously, patient and NGS’s integrated potential completely permeated only into 

throughout our medical research, systems. but it is now turning 

the So corner where and rapidly do we moving stand into now? the Previclinicalously, space. NGS’s One example potential is permeated prenatal scans, only 

which throughout will begin research, in earnest but across it is now thousands turning 

of 

the 

newborns 

corner 

in 

and 

2015. 

rapidly 

This 

moving 

data will 

into 

provide 

the 

clinical space. One example is prenatal 

a genetic roadmap for all stages of life. 

scans, which will begin in earnest across 

While this application of NGS provides 

thousands of newborns in 2015. This 

invaluable data will provide patient data, a genetic the data roadmap is com- for 

plex—exponentially all stages of life. increasing a hospital’s 

data While management this application and analytic of burden. NGS pro- 

It vides also requires invaluable significant patient standardization, 

data, the data 

commoditization is complex—exponentially and automation increasing of NGS a 

analytics hospital’s as data applied management to medicine. and analytic 

Unfortunately, burden. It also with requires multiple sequences, significant 

multiple standardization, analyses and commoditization a holistic perspecand 

tive 

automation 

of the applicability 

of NGS analytics 

of genomics 

as applied 

into 

to medicine. 

medicine now on tap, the technologies 

Unfortunately, with multiple sequenc- 

currently available in the clinics simply 

es, multiple analyses and a holistic 

cannot perspective support of the influx applicability of data of required genom- 

for ics analysis. into medicine Couple now this with on tap, the increasing the tech- 

consumerization nologies currently of medicine, available and in the we clinics are 

simply cannot support the influx of data 

required for analysis. Couple this with the 

increasing consumerization of medicine 

left and with we are existing left legacy with existing technologies legacy that tech- 

are nologies just too that brittle are and just too too cost-ineffective. 

brittle and too 

cost-ineffective. 

Where So where does the does solution the solution lie? lie? Not 

Not likely likely in million in million dollar systems that that will 

will 

never never scale scale or reach and reach the necessary the necessary levels of 

adoption. levels of Delivering adoption. a Appistry’s focused solution Ayrris/BIO that 

provides 

provides 

exact 

a focused 

answers 

solution 

to the 

that 

questions 

provides 

the exact answer to the questions com- 

commonly asked by both the clinician 

monly asked by both the clinician and the 

and the patient, Appistry’s Ayrris / BIO is 

patient, turning the myriad of available 

turning 

data into 

the 

actionable 

myriad of available 

intelligence. 

data into 

actionable Ayrris/BIO intelligence. will enable the application 

Ayrris of NGS / BIO as enables value-added the application analysis 

of built NGS into as value-added existing medical analysis processing built 

into and existing the targeting medical of processing drugs relative and the to 

targeting disease subtyping of drugs relative identified to disease via genetic 

subtyping testing. Ayrris/BIO identified via will genetic also testing. speed the 

Ayrris ability / to BIO target also drugs speeds via the synthesis. ability to Over 

target time, NGS drugs will via scale synthesis. to meet Over the time, needs NGS 

and expertise of the hospital—and this 

will scale to meet the needs and expertise 

includes custom-built appliances such 

of the hospital. This includes custom-built 

as Ayrris/BIO that will run in parallel with 

appliances, 

existing EMR 

such 

systems. 

as Ayrris 

Costs 

/ BIO, 

for 

which 

NGS 

run 

will 

in decrease parallel with to less existing than EMR $5 systems. per month Costs per 

for patient, NGS will with decrease an all-in to less cost than of less $5 per than 

Full-spectrum 

analyses of 

genetic data, 

starting at 

$ 99 per patient. 

$1000 (including analysis) per year. 

The vision is clear: NGS applied to 

medicine is no longer a research project, 

but month is per an patient, evolving with clinically an all-in actionable cost of less 

activity. than $1000 The (including market for analysis) this is turning per year. into 

a $100bn The vision industry, is clear: with NGS many applied multiples 

of to medicine growth per is no year. longer Appistry’s a research Ayrris/ project, 

BIO but is technology an evolving provides clinically actionable a full-spectrum 

analyses activity. The of market genetic for this data, is turning from basic into 

Exome a $100bn to Whole industry, Genome with many to RNA multiples analysis of 

at growth class per leading year. Appistry’s quality and Ayrris best / BIO in tech- the 

world prices, starting at $99 per patient 

nology provides full-spectrum analyses of 

analysis. These medically actionable 

genetic data, from basic Exome to Whole 

analyses are available as a service or 

via 

Genome 

an appliance 

to RNA analysis 

today. 

at class leading 

quality and best-in-the-world prices, 

starting at $99 per patient analysis. These 

Appistry medically actionable – Discovery analyses at are the available 

pace today as of a human self-hosted thought appliance that can 

run in your existing environment or via our 

remotely hosted pay-per-use service. 

Discovery at the pace 

of human thought 

For more information: 


www.Appistry.com www.Appistry.com 

314.336.5080 314.336.5080 

info@appistry.com info@appistry.com 

www.bio-itworld.com NOVEMBER | DECEMBER 2011 BIO•IT WORLD [ 31 

www.bio-itworld.com NOVEMBER | DECEMBER 2011 BIO•IT WORLD [ 1 ]

Feature 

i A next-generation 

sequencing company 

introduces a new Cloud portal 

for its new benchtop 

sequencer 

i A cloud computing 

firm hosts a key bioscience 

database in the Google 

cloud 

CONTENTS 

By Kevin Davies 

IN 

MANY WAYS, CLOUD COMPUTING has become 

an ever-present commodity since Bio•IT World published 

a special issue on the subject (Nov 2009). In 

September 2011, we held our first standalone conference 

on the topic. Experts—users and vendors 

alike—gathered for two days of sharing insights and 

progress. The takeaway was that more and more users were comfortable 

with the flexibility, cost, and even security afforded by the cloud. And while 

Amazon’s omniscient cloud capabilities were a recurring theme, what was 

even more impressive was the growing ecosystem of commercial and opensource 

initiatives offering a host of cloud-based services and applications. 


THE UTILIT Y OF 

CLOUD 

COMPUTING 

i An Ivy League school launches 

an on-demand research computing 

service running an open-source 

cloud platform 

i A software provider 

offers $10,000 in free compute 

time to the most imaginative 

biomedical question 

i A big pharma 

company spins up a 30,000-core 

supercomputer in the cloud

Amylin Pharmaceuticals’ Steve Philpott 

was one of the first biotech CIOs to 

enthusiastically embrace “the big switch” 

to the cloud. “Our IT cost infrastructure 

is 50% less than when we started [in 

2008]. My CFO really likes us!” Philpott 

said. “The box has disappeared… Do you 

care where your last Google search came 

from? No.” 

But the cloud still raises doubts and 

concerns. A major issue, discussed below, 

surrounds security and regulation. Another 

is whether the cloud can truly 

handle the masses of next-gen data that 

is being generated. “Can the cloud satisfy 

the requirement or can the requirement 

satisfy reality?” asks Eagle Genomics 

CEO Richard Holland. “Sometimes it’s 

not the cloud at all but the Internet—the 

whole concept of the network and trying 

to transfer that amount of data. Do you 

really need to be transferring that much 

data in the first place? I think people are 

generating so much data now, and they’re 

expecting to do with it what they always 

could, and that just might not be possible. 

You might have to rethink the whole paradigm 

of how this works.” 

From A to Z 

When it comes to the cloud, it boils down 

to infrastructure-as-a-service, and that 

means Amazon, “pretty much by default,” 

says Holland (see, “Eagle Eye on 

the Cloud”). That said, there are many 

other players, including Rackspace, Penguin, 

GoGrid, Nimbus, and Eucalyptus 

(open-source). 

Johnson & Johnson’s John Bowles said 

that the Amazon environment was “an 

eye-opener in terms of infrastructureas-a-service… 

Seldom mentioned in big 

pharma is the “opportunity cost.” If it 

takes six months to get a machine through 

CapX, there’s no cost for that time.” J&J’s 

tranSMART knowledge base (see, “Running 

tranSMART for the Drug Development 

Marathon,” Bio•IT World, Jan 2010) 

went live two years ago. “Without the 

cloud environment, we’d still be arguing!” 

said Bowles. 

According to Amazon Web Services 

(AWS) senior evangelist, Jeff Barr, AWS 

is like electricity—a utility that you pay 

as you use. “On demand, run by experts,” 

he said. With its roots tracing back to the 

Amazon 

Machine 

Image (AMI) 

CloudWatch 

Auto 

Scaling 

Region 

Availability Zone 

EC2 Instance 

Security 

Group(s) 

Elastic IP 

Address 

Load Balancing 

Amazon’s EC2 architecture remains a widely popular Infrastructure-as-a-Service. 

Eagle Eye on the Cloud 

Richard Holland, CEO of the fast-growing 

UK consultancy Eagle Genomics, 

can attest to the growing use of cloud 

computing. From a strength working 

with pharma and biotech in pipelines 

and data analysis, Holland says business 

is growing and diversifying into areas 

such as plant science and animal health. 

“We’re open-source, very transparent. 

We use the best tool for the job. 

Many customers want pilots or proofof-concepts, 

eager to give the cloud a go, 

let us demonstrate how it can work for 

them. When those succeed, which they 

usually do, we make them into production 

systems. Other customers are more 

forward thinking—they’ve already made 

commitment and have more detailed 

projects.” 

Eagle has collaborated with Taverna, 

the open-source workflow tool (see, “Democratizing 

Informatics for the Long- 

Tail Scientist,” Bio•IT World, March 

2011), in a partnership with the University 

of Manchester, handling genetic data 

for diagnostics. Another big customer 

specializes in microbial genome analysis, 

and is seeking to graduate from a 

“creaking cluster” to the cloud. Eagle is 

also working with the Pistoia Alliance, 

Elastic 

Block 

Storage 

EBS 

Snapshot 

Amazon S3 

Ephemeral 

Storage 

EBS 

Snapshot 

where Eagle will help run a competition 

to compress next-gen sequencing data. 

Holland says the major stumbling 

block to wider adoption of cloud computing 

is not so much getting data up 

and down (“It’s not a solved problem, but 

there are some decent solutions.”) but 

“implementing additional security layers 

on top of Amazon to convince people 

it is secure. Amazon’s infrastructure is 

perfectly fine, but they don’t make it any 

easier to implement additional layers 

above the operation system [than anyone 

else].” 

Eagle hasn’t had the bandwidth to 

tackle any clinical data projects thus 

far. “It’s straightforward to set up the IT 

system,” says Holland, “but it’s the paper 

trail that goes with it. We’re too small to 

handle that at this stage.” That would appear 

to be the provenance of the global 

consulting firms, “but they don’t have the 

cloud expertise.” Hopefully the two will 

come together at some point. 

Holland said he was struck by how 

popular open-source software is in 

the cloud. Many commercial licensing 

models haven’t adopted, he said. “Opensource 

is the only thing that can cope at 

the moment.” K.D. 


CONTENTS

CONTENTS 

Feature 

1960s (commodity computing, mass-produced 

computers), Barr said: “We’re past 

the innovators and early adopters—we’re 

at the early majority point.” 

The advantages of the cloud are well 

known by now: no capital expenditure, 

pay-as-you-go, elastic capacity, and (in 

principle) improved time to market. “You 

can iterate and cycle more quickly. People 

love this elasticity,” said Barr. Trying to 

predict demand using a terrestrial data 

center is notoriously tricky, and inevitably 

leads to either an “opportunity cost” 

(compute power laying idle) or an inability 

to serve customers (demand exceeds 

supply). “The cloud can scale up or down, 

so the infrastructure matches the actual 

demand,” he said. 

The Amazon cloud is spread across 

six geographic regions: the US (East and 

West Coast), Singapore, Tokyo, Europe, 

and one reserved for the U.S. federal 

government. Users have full control over 

where their data are stored and processed. 

“If you have regulatory issues and 

your data must remain in Europe, that’s 

(continued on page 36) 

Genome Analysis 

in the Cloud 

According to Harvard Medical School’s 

Dennis Wall, whole-genome analysis 

in the cloud is poised to have the same 

impact as the development of the autoanalyzer 

in the 1950s, a now ubiquitous 

device for blood analysis. 

Earlier this year, Wall, Peter Tonellato, 

and colleagues built a model to estimate 

the cloud runtime based on the size and 

complexity of human genomes being 

compared, to pre-determine the optimal 

order of the jobs being submitted. For 

example, an experiment requiring nearly 

250,000 genome-to-genome comparisons 

on Amazon EC2 required some 200 

hours, costing $8,000—about 40% less 

than expected. This highly adaptable 

model is “potentially of significant benefit 

to labs seeking to take advantage of the 

cloud as an alternative to local computing 

infrastructure,” Wall blogged earlier 

Chris Dagdigian 


MARK GABRENYA/FILE 

FUSARO VA ET AL. PLOS COMPUT BIOL 7(8): E1002147 

A 

Prototyping 

Amazon Web Services 

7 GB memory 

1.7 TB disk space 

$0.68/CPU hr. 

Work Flow Overview 

Truncated test set of NGS reads. 

2 �les with 10,000 reads per �le. 

[3 GB ref. genome + 2.2 MB read �les] 

Align reads and determine SNP 

calls using MAQ. 

[5 hours] 

Final alignment output �le 

[1 MB] 

Internet 

$3.85 $49.60 $320.10 

The cloud is being deployed for clinical whole genome analysis at Harvard Medical School. 

this year. 

Last summer, the same group published 

a report in PLoS Computational 

Biology outlining the steps required to 

B 

C 

Developing Scalable Application Scaled Application 

Amazon Web Services Amazon Web Services 

Cluster management 

software 

Development and testing 

Work Flow Overview Work Flow Overview 

Test set of NGS reads. 

32 �les with 1 million reads per �le. 

[3.34 GB read �les] 



[12 hours] 


[1.3 GB] 

Whole genome set of NGS reads. 

606 �les with ~7 million reads per �le. 

[370 GB read �les] 



[10 hours * 38 instances] 


[142 GB] 

Use your local computer to connect to instances using secure shell (ssh) 

and transfer data using secure copy (scp). 

perform a whole-genome analysis in the 

cloud. A full-scale alignment of a human 

genome took about 10 hours on 36 instances 

for a modest cost of $320. K.D. 

x N

The 2012 Bio•IT World Best Practices 

competition has released its call for entries. 

Since 2003, Bio•IT World’s Best Practices 

competition has been recognizing outstanding 

examples of technology and strategic innovation 

initiatives across the drug discovery enterprise. 

The awards attract an elite group of 

life science professionals: executives, 

entrepreneurs, innovators, researchers 

and clinicians responsible for developing 

and implementing innovative solutions for 

streamlining the drug development and clinical 

trial process. Bio•IT World’s distinguished peerreview 

panel of judges has reviewed more than 

400 entries in the program’s history. 

Entries will be accepted in six categories: 

Clinical & Health-IT; IT Infrastructure/HPC; 

Informatics; Knowledge Management; 

Research & Drug Discovery; and Personalized 

& Translational Medicine. The 2012 winners will 

receive a unique crystal award to be presented 

at the Bio-IT World Conference & Expo in 

Boston, April 24-26, 2012. Winners and entrants 

will also be featured in Bio•IT World. 

For more information on the program and to download the entry form, 

please visit www.bio-itworld.com/bestpractices. 

Deadline for Entry: January 13, 2012 | Early Bird Deadline: December 16, 2011

CONTENTS 

Feature 

(continued from page 34) 

fine,” he said. In addition to paying on demand, 

users can buy spot price instances, 

the price changing minute to minute. 

“This enables you to bid on unused Amazon 

EC2 capacity,” said Barr. “You can use 

this to obtain capacity very economically.” 

A recently published example comes 

from Peter Tonellato’s group at Harvard 

Medical School, building a pipeline for 

clinical genome analysis in the cloud (see, 

“Genome Analysis in the Cloud”). 

Barr was excited about Amazon’s new 

relational database service, which allows 

users to launch a new database in a matter 

of seconds. Compare that to a MySQL or 

Oracle database, Barr said, which might 

take a year to get up and running. This 

could allow users to offload common 

administration tasks—OS and database 

upgrades, backups etc.—to AWS. Other 

new initiatives include Cloud Formation 

and AWS Elastic Beanstalk (a simple way 

to deploy/manage applications). “We’ve 

moved from individual resources to entire 

apps, entire stacks, being programmable 

and scriptable,” said Barr. 

A recent announcement by DNAnexus 

(see p. 41) revealed that a mirror of 

the NIH Short Read Archive of DNA 

sequence data will be hosted on the 

Google cloud. BioTeam principal Chris 

Dagdigian says the platform differs from 

Amazon’s. “Google has a more integrated 

platform that you run on top of, while 

AWS offers infrastructure elements that 

can be assembled and combined in many 

different ways,” said Dagdigian. “If the 

Google/DNAnexus collaboration delivers 

an easy-to-use compute platform with 

integrated ‘big data’ support, it could be 

quite interesting.” 

Dagdigian remains a fervent backer 

of Amazon’s cloud infrastructure. “VMware—that’s 

not a cloud,” he told the 

crowd in La Jolla. “If you don’t have an 

API, or self-service, or email to humans, 

it’s not a cloud. If you have a 50% failure 

rate, it’s a stupid cloud.” 

Dagdigian sees “a whole new world” 

when it comes to moving high-performance 

computing (HPC) into the cloud. 

Instead of building a generic system 

accessible by a few groups, one can 

now stand up dedicated, individually 

optimized resources for each HPC use 

Cycle Time 


Earlier this year, Cycle Computing 

span up 10,000 cores for Genentech 

for $1,060/hour. The company 

trumped that with a 30,000-core 

cluster spanning three regions for 

$1,280/hr for a leading 

pharma customer. “Why 

use 30,000 cores? It’s 

no longer about utilization,” 

said CEO Jason 

Stowe. Take data reanalysis—the 

cloud makes 

it possible to test new 

algorithms on historical 

data in a way never possible 

before. 

Cycle recently announced 

that it will 

partner with Pacific Biosciences 

to optimize the 

cloud-based version of PacBio’s SMRT 

Analysis software, supporting a workflow 

that includes sample preparation, 

sequencing and completed data analysis 

in less than one day. A beta version 

of the solution is expected by the end 

of 2011. 

In terms of managing data, Stowe 

spoke enthusiastically about Opscode’s 

Chef software for automating the 

cloud. “BioTeam discovered Chef a 

couple of years ago, and we’re equally 

big fans. It’s very developer friendly,” 

said Stowe. “It would be much more 

difficult to run at our scales without the 

thought that’s been put into Chef from 

the start,” added Cycle’s Andrew Ka- 

case. When it comes to hybrid clouds 

and “cloud bursting,” Dagdigian recommended 

a buy-don’t-build strategy. Data 

movement is a pain. “I’m a fan of open 

source, but if you’re doing it, buy rather 

than build,” he said. Companies such as 

Cycle Computing (see, “Cycle Time”) and 

Univa UD have happy customers, he said. 

“You can’t rewrite everything,” said 

Dagdigian. “Life sciences informatics 

has hundreds of codes that will never be 

rewritten. They’ll never change and will 

be needed for years to come.” The future 


Jason Stowe 

zmorek. In keeping with the culinary 

theme, Cycle uses Grill as a monitoring 

solution for any Chef infrastructure in 

the cloud. 

Stowe also announced plans to offer 

$10,000 in free computing 

time in a competition 

“to help researchers 

answer questions that 

will help humanity.” All 

the attention on how 

many cores could potentially 

be spun up in 

the cloud left Stowe a 

little puzzled. “I worried 

that in all this glitter, 

we would miss what 

is truly gold,” he said. 

“Researchers are in the 

long-term habit of sizing 

their questions to the compute cluster 

they have, rather than the other way 

around. This isn’t the way we should 

work. We should provision compute at 

the scale the questions need.” 

Stowe wants “to wreck the status 

quo of HPC clusters and computational 

science. We will enable those crazy 

questions from the misfit geniuses, the 

ones so big that you would never even 

ask them… “This is about to get truly 

exciting… because someone is going to 

take these clusters and cure cancer, or 

Alzheimer’s, or my personal affliction, 

type 1 diabetes. And hopefully cure 

them faster because they have better 

tools.” K.D. 

of Big Data, he said, lies with tools such 

as Hadoop and Map Reduce. “Small 

groups will write such apps, publish, 

open-source, and we’ll all plagiarize from 

them,” he said. 

While many users want high availability 

and resiliency, Dagdigian said that 

“HPC nerds” want speed, “I’d pay Amazon 

extra if they’d guarantee servers in the 

same rack,” he said. “HPC is an edge case 

for obscene-scale IaaS clouds. We need to 

engineer around this. We have to know 

where the bottlenecks are.”

Assay Depot’s Cloud Services 

“Our goal is to empower the researcher. 

There’s no way for the average 

scientist to explore the world of services 

available to them.” So says Chris 

Petersen, co-founder and CIO of Assay 

Depot, which currently boasts more 

than 600 vendors and several thousand 

services on its website. The goal 

is to offer researchers a comprehensive 

list of services for pharma, such as 

animal models, antibodies, compound 

synthesis, and allow them to communicate 

and rate vendors. 

Assay Depot also builds white-label 

or private versions of the marketplace 

for individual pharma clients. Pfizer 

and two other big pharmas have already 

signed up, with other pilot projects 

underway. “They can customize it 

and integrate with finance or sample 

management systems,” says Petersen. 

“And they can create private reviews, 

to learn from your colleagues’ past 

experiences.” 

“It’s all about capturing institutional 

knowledge. Some researchers might 

know a lot about a particular vendor in 

China that other colleagues might not 

know. In massive companies, many 

groups don’t know what other groups 

Dagdigian couldn’t stop raving about 

MIT’s StarCluster (“It’s magical,” he said.), 

Opscode Chef, and GlusterFS (now part 

of Red Hat), particularly for scale-out 

NAS on the cloud. And he said CODO- 

NiS was a promising start-up for storage 

and security. As for future applications of 

cloud computing, Dagdigian insisted that 

Amazon itself was “no bottleneck—it’s 

always the server or the Internet.” “Directto-S3” 

file transfer solutions from Aspera 

(see, “Aspera’s fasp Track for High-Speed 

Data Delivery,” Bio•IT World, Nov 2010) 

also looked very promising. 

Leading the Charge 

With the need to maximize IT efficiency, 

Amylin’s Steve Philpott led the charge to 

rethink IT under considerable financial 

pressure (see, “Amylin, Amazon, and 

the Cloud,” Bio•IT World, Nov 2009). 

are doing.” Vendors join Assay Depot 

for free, and can respond to requests 

for information. Assay Depot charges 

a small annual fee if they want to list 

their services, and pharmas pay a hosting 

fee if they want a private version. 

Assay Depot’s pharma prospects 

were initially very suspicious about 

the cloud, says Petersen. “There was 

some pushback! We got them to use 

it by telling them we’d give them their 

own server in the cloud behind the 

firewall. We host [private] marketplaces 

on Amazon EC2, each hosted 

on its own set of servers in a security 

group. Often in the past, when we 

used to say EC2 they’d get worried; 

now they say, check, we’ve already 

audited them.” 

Petersen enthusiastically endorsed 

Opscode’s Chef. “It is how we do the 

automated provisioning of our server. I 

can’t stress enough how important it’s 

been to automate the infrastructure… 

The cloud has blurred the line between 

operations and software development, 

which really helps a startup. Since 

Amazon has taken that hardware and 

turned it into software, that line has 

really blurred.” K.D. 

“We have access to tremendous capabilities 

without having to build capabilities—10,000 

cores, new apps cheap,” said 

Amylin’s Todd Stewart. “Some tools— 

manufacturing, ERP, etc.—will always be 

in the data center. But let’s 

find process that will work 

in the cloud.” 

With both campus data 

centers full, Amylin led to 

pilot projects, including 

more than a dozen softwareas-a-service 

processes. Stewart 

noted that there was only 

one validated app in the 

cloud. “In general, that’s still 

Steve Philpott 

something we’re struggling 

with,” he said. CRM and call center apps 

have moved over. And Amylin has used 

Nirvanix Cloud storage for two years—“a 

cubby hole on the Internet,” said Stew- 

FRANK ROGOZIENSKI/FILE 

Chris Peterson 

art. “We hope to go tapeless on backups 

shortly.” 

“Chef is something we’ve had a look 

at,” says Eagle Genomics’ Holland. “As you 

scale up, it becomes less and less practical 

to use anything else, to be 

honest. You could write it 

yourself with a bunch of 

Python scripts, but someone 

else has done it, so why 

bother?!” 

“We launched a 10,000node 

cluster with one click 

[using Chef],” said Cycle 

Computing’s Andrew 

Kaczorek. 

Chris Brown, Opscode’s 

chief technical officer (and co-developer 

of Amazon EC2) said: “We’re software 

architects and system administrators. 

We’ve run Amazon.com and Xbox live. 


CONTENTS

CONTENTS 

Feature 

[We’re good at] automating infrastructure 

at scale.” The cloud, Brown said, is 

not necessarily cheaper than standard 

hosting. “Do you have the money, time, 

experience? What are you willing to pay 

for?” he asked. “We take the experience 

and plug it in for you. You want to manage 

1,000 machines instantly. Google, 

Amazon—they have 100 people. Where 

can you find a team?” 

Chef is many things: a library for 

configuration management, a systems 

integration platform, and an API for the 

entire infrastructure. “Our mantra is to 

enable you to construct or reconstruct 

your business from nothing but a source 

code repository, an application data 

backup, and machines.” 

“Big pharma is concerned about auditing: 

now we can show a snapshot of 

cookbooks running on a node. We can 

reproduce and launch a cluster that mirrors 

what it was at that date and time. It is 

very powerful,” said Kaczorek. 

More Clouds 

The number of cloud applications and 

offerings is too many to list. Appistry’s 

new Ayrris Bio offering is poised to make 

a big impact on life sciences organizations 

(see, “Appistry’s Fabric Computing”). 

Assay Depot hosts fully audited, private 

marketplaces for pharma clients (see, 

“Assay Depot’s Cloud Services”). Complete 

Genomics selected the Bionimbus opensource 

community cloud as a mirror for 

a major genome dataset. The University 

of Maryland’s CloVR is a portable virtual 

machine launched on a desktop that can 

manage additional resources on the cloud 

(EC2, academic clouds) for large-scale 

sequence analysis. 

The San Diego Supercomputer Center 

is rolling out a cloud, “a private data 

storage cloud to enable the presentation 

and sharing of scientific data, with rental 

and owner pricing,” said SDSC’s Richard 

Moore. It will have an elastic design with 

an initial capacity of 2 petabytes, although 

the emphasis will be more on access and 

sharing. Chemaxon’s David Deng presented 

a collaboration with GlaxoSmithKline 

(GSK) on cloud computing, in which 

13,500 potential anti-malarial drugs have 

been made free available, hosted on EC2. 

Users access the data using ChemAxon’s 


Appistry’s Fabric Computing 

Appistry (the name derives from the exome, RNA-seq and whole-genome 

phrase “Application Artistry”) offers a analysis. 

variety of cloud computing offerings in “We have everything set up and 

life sciences and bioinformatics. Michael ready to go right now,” says Groner. “Give 

Groner, co-founder and chief architect, us your files; we’re ready.” As for data de- 

said the company’s mislivery, 

Appistry is getting 

sion came from the belief 

hooked up on Internet 2, 

that engineers “spend 

but hard drive delivery 

too much time building 

works well. Groner says 

in scale management 

the company is offering 

adaptability into our 

“head-snapping prices” 

software, more than the 

as low as $250/run and 

value add we want to 

alignments for less than 

build in. That seemed 

$1,000. 

wrong.” 

Groner ticks off sev- 

Groner says his coeral 

advantages of Apfounder, 

Bob Lazzano, 

recognized the value of 

Michael Groner 

pistry’s architecture. “We 

don’t rely on virtualiza- 

linking cheap computers via software tion—our software is as close to the bare 

back in 2000. “He had insight that metal as possible (unlike Amazon and 

predicted cloud computing seven years other public clouds).” But the one he 

before it took off!” says Groner. He called stresses is the usage of computational 

it “fabric computing,” the idea being storage, or as Groner puts it, “where 

that Appistry hides hardware beneath we move work to the data.” Minimizing 

the fabric so that it looks like a single data movement is essential to solving 

computational entity. “We recognize that Big Data analytics in less time, he says. 

our favorite phrase lost,” says Groner, not “Our execution environment applies 

sounding too worried. 

our HPC patterns on to existing, un- 

That sounds a bit like Al Gore inmodified tools to execute subsets of the 

venting the Internet, but Appistry of- analytics on the ‘best’ machine possible,” 

fers a software tier that ties machines which is often the machine holding the 

together. “It makes multiple machines data to be processed. 

act as one, and hides the failures/details In addition to running data in its own 

from you, so you can have your ma- environment, Appistry also resells the 

chines adapt, scale, and modify to your appliance (up to a single rack) and cloud 

environment, and you can focus on the architecture, so users with very high data 

value of your application,” says Groner. volumes or security issues can set up the 

Appistry is harnessing its experience same system in their own environment. 

in clouds, high-performance comput- “We realized that for some solutions, 

ing and analytics—FedEx is one of its instead of just taking a tool perspective, 

biggest customers—with its new life sci- we could sell the complete solution,” says 

ences offering called Ayrris Bio. Appistry Groner. “We hired some bioinformati- 

offers its own public service based on cians and put together this complete 

its cloud on a per usage basis, including solution.” K.D. 

Instant JChem database management 

tool, requiring no local software installation. 

Deng admitted that security was not 

a huge issue in this particular case, but 

added his colleagues are eager to set up 

other collaborations. 

Former Microsoft executive and BioIT 

Alliance founder Don Rule wrapped up 

the La Jolla conference. “Cloud computing 

is a very powerful enabler despite the 

hype,” said Rule. “It’s an important enabler 

for personalized medicine.” Ironically, 

Rule is experimenting with EC2 to run an 

encrypted HIPAA-compliant database. •

CONTENTS 

Next-Gen Data 

New Rules for Archon 

Genomics X Prize 

Competition kicks off in 

2013 with Medco as 

presenting sponsor. 


The Archon Genomics X Prize, 

which offers a $10 million purse 

for a significant breakthrough in 

the whole genome sequencing of 

100 genomes, has announced adjustments 

to its rules, criteria, and timing, as 

well as officially welcoming a major new 

sponsor—Medco Health Solutions. 

The new competition will kick off on 

January 3, 2013, and end 30 days later. If 

there is no grand prize winner, the purse 

will be split between category winners for 

accuracy, completeness and haplotype 

phasing. “Although most races can only 

have one winner, we believe that after this 

race, the competition will benefit and entire 

industry,” wrote X PRIZE Foundation 

executives Larry Kedes and Grant Campany 

in a Nature Genetics commentary 

detailing the new rules. 

Launched in 2006 to great fanfare, 

the original competition rules stated that 

entrants had to sequence 100 human 

genomes in ten days or less at $10,000/ 

genome to very high accuracy. The prize 

was initially funded by a Canadian diamond 

hunter named Stewart Blusson and 

his wife Marilyn. Further funding was 

supplied by genome sequencing pioneer 

J. Craig Venter, who in 2003 pledged 

$500,000 from his foundation for a 

major breakthrough in next-generation 

sequencing. 

But only eight organizations registered 

to compete, including 454 Life Sciences, 

ZS Genetics, and an offshoot of George 

Church’s Personal Genome Project. Some 

observers suggested that the stringency 

of the rules might have deterred groups 

from entering. 

“I hope this is the beginning of a new 

race for the human genome,” said Ryan 


Phelan, the president and founder of 

DNA Direct by Medco. “Getting a medical 

grade genome is essential in translating 

the human genome into clinical practice.” 

Making the Grade 

In the announcement made last month, 

the X Prize Foundation announced several 

key changes to the structure of the 

competition. 

First, the competition rules have relaxed 

in some cases, tightened in others. 

Teams will be judged on accuracy, cost, 

speed and completeness of genome sequencing. 

The organizers believe that “the 

competition’s audacious target criteria for 

accuracy and completeness 

of sequencing could 

define for the first time a 

‘medical grade’ genome.” 

Teams are now given 

30 days to sequence the 

genomes of the 100 subjects, 

but the cost has 

been cut to $1,000 or less 

per genome, a reflection 

that mainstream NGS 

platforms are already 

well under the original 

$10,000 X PRIZE 

threshold. The genomes 

must be sequenced to an overall accuracy 

of 99.9999%, or no more than one error 

per million base pairs. 

Second, the pharmacy benefits manager 

Medco Health Solutions, has joined 

as the competition’s presenting sponsor. 

The prize will now be known as the 

Archon Genomics X PRIZE presented 

by Medco. Medco Research Institute 

president Felix Frueh said that the new 

prize “is the game changer that’s needed 

to reach that final mile and transform 

the full promise of genomic research into 

practical clinical care.” 

Third, the 100 genomes to be sequenced 

will be those of volunteering 

(and consented) centenarians, rather 

than the eclectic group of celebrities, 

T eams will be 

judged on 

accuracy, cost, 

speed and 

completeness 

of sequencing. 

scientists and other volunteers originally 

envisioned. These centenarians, or the 

‘Medco 100 Over 100,’ are, in the words 

of the X PRIZE press release, “donating 

their genome to this competition in order 

to further medical science.” 

“Our goal is to assemble an ethnically 

diverse group of ‘genomic pioneers’ who 

are at least 105 years of age,” said Campany, 

senior director of the genomics X 

prize. “Such individuals who have evaded 

all of the common diseases associated 

with aging are effectively supercontrols 

whose genomes deserve to be scrutinized 

in contrast to the genotypes of the many 

disease cohorts currently under investigation,” 

commented the editors of Nature 

Genetics. 

The sequencing results will be compiled 

into a public database (such as 

dbGaP), raising the notion that the 

resulting data might help elucidate the 

presence of so-called ‘wellness’ genes. It 

should be noted, however, 

that several other 

initiatives to parse the 

genomes of centenarians 

are already underway. 

For example, Complete 

Genomics and Scripps 

Health announced earlier 

this month that they 

will collaborate on a 

project to sequence the 

genomes of 1,000 ‘wellderly’ 

individuals. 

Medco’s Phelan said 

the company has been 

“driving innovation around personalized 

medicine for at least five years,” particularly 

in the area of genetic testing and 

pharmacogenomics. “Medco was one of 

the first, and is still one of the only, Fortune 

500 companies, to really embrace 

personalized medicine to this degree,” 

says Phelan. 

With the rapid developments in genome 

sequencing and interpretation, 

“Our sense was that we could help move 

the needle in this area. How could we not 

help usher in this new era of personalized 

medicine?... 

“Hopefully we’ll see a big explosion in 

the bioinformatics, getting this information 

then how do we interpret it? That’s 

the biggest white space.” •

DNAnexus to Mirror SRA 

Database in Google Cloud 

Mirror site for NCBI 

sequence repository 

facing funding challenges. 


DNAnexus will offer free hosting 

and access to the Short Read 

Archive (SRA), the funding-challenged 

trove of NGS read data 

hosted by the National Center for Biotechnology 

Information (NCBI). 

Earlier this year, NCBI announced 

that it would be phasing 

out funding for the 

SRA. “We realized this 

would be a huge loss for 

the community, but a 

great opportunity for us 

to step up and preserve 

it,” said DNAnexus cofounder 

and CEO, Andreas 

Sundquist. 

DNAnexus will host 

a publicly available 

copy of the SRA repository 

on Google’s Cloud 

Storage infrastructure 

(see sra.dnanexus. 

com). 

According to NCBI’s 

Jim Ostell, NCBI remains 

the primary archive for SRA, but 

he welcomed the offer from a reliable 

commercial source to provide an alternative 

hosting environment. “We agreed 

with them that there was certainly a need 

for nice packaged tool sets for people 

working with high-throughput sequence,” 

said Ostell. “If anyone finds it useful, 

either to explore and analyze the public 

data, or to work on pre-release data of 

their own, then that’s good.” 

However, Ostell stressed that DNAnexus 

is not taking over SRA. “They are not 

an archive, they don’t issue accession 

numbers, and are not part of any official 

NIH data publishing process… It’s been a 

strictly technical issue of transferring data, 

working with Google, and getting their 

platform in place.” 

While central NIH funding for the 

SRA is ending this month, NCBI will 

still accept certain classes of SRA data 

that don’t necessarily generate massive 

amounts of data, but are important for 

the scientific record. Some individual 

NIH institutes have agreed to fund NCBI 

directly to keep SRA going for their studies, 

says Ostell. 

“We’re doing this to help NCBI with 

their mission,” explained Sundquist. “Our 

hope is that the hosted version of the 

Search Across Different Objects 

SRA will provide a complementary way 

for researchers to access these data.” He 

projects that the SRA repository will grow 

tenfold each year. “The SRA has done a 

tremendous service to the research community 

by capturing these data and we 

want to help preserve it.” 

Sundquist says DNAnexus has cleaned 

up the SRA interface as “it’s been a little 

cumbersome to use.” Eventually, researchers 

might be able to submit data direct to 

DNAnexus to host in the SRA. “There is 

no sign up required for anyone who wants 

to use SRA.” 

“No-one thinks the government 

should be providing access in perpetu- 

ity,” says Sundquist. “When the SRA was 

originally built, it was a different era, 

a different volume of data.” Sundquist 

expects the archive to swell to hundreds, 

possibly thousands of times its present 

size in the years ahead. “[SRA] will be 

a tiny bit of data compared to five years 

from now. Think what it will be like when 

we’re sequencing millions or tens of millions 

of genomes!” 

Google Backing 

DNAnexus also announced it had received 

funding from Google Ventures (see 

below) in a $15-million round, a relationship 

that Sundquist says shows Google’s 

commitment to help “democratize DNA 

data.” A copy of all the data in the public 

SRA will be hosted in Google Cloud Storage. 

“The DNAnexus SRA website is an 

example of a ‘big data’ initiative that benefits 

from rethinking 

the interface in a 100% 

web-enabled world,” 

said Eric Morse, head 

Single Search Box 

DNAnexus is offering free access and easy navigation to the SRA database. 

Ranked List of 

Search Results 

of business development, 

Google Cloud 

Storage. 

The Google tie-in 

is interesting, as most 

of the DNAnexus infrastructure 

is built on 

Amazon’s EC2 Cloud. 

“Now we’re working 

with both Amazon 

and Google on providing 

access to large genomic 

datasets,” notes 

Sundquist. 

Sundquist also an- 

nounced a significant cut in pricing for 

academic customers. “In some ways, the 

academic community is the key to driving 

this space forward. Because of the great 

response, we’ve slashed our prices substantially 

by half for academia, effective 

immediately.” 

Sundquist says DNAnexus is “absolutely 

focused” on genome interpretation, recognizing 

a huge opportunity for growth. 

“For us, it’s not just about the ‘$1 million 

interpretation’ for one genome, you have 

to think about this interpretation and 

scale it up to thousands of genomes. That’s 

a whole different domain, a huge space 

that no-one has built anything around.” • 


CONTENTS

CONTENTS 

Next-Gen Data 

Inova/Complete Partnership 

Signals ‘Next-Gen Medicine’ 

Initial agreement focuses on pre-term babies. 


The CEO of the Inova Translational 

Medicine Institute (ITMI), which recently 

signed a major deal to sequence the 

genomes of hundreds of pre-term babies, 

has shed light on the motivation and goals 

of the partnership. 

The Complete Genomics deal with 

ITMI calls for the sequencing of 1,500 genomes—including 

250 pre-term babies, 

their parents and an equal number of 

controls. Complete Genomics will begin 

delivering sequencing results to ITMI in 

the next 2-3 months and expects to finish 

most of the 1,500 genomes in the first 

quarter of 2012. 

ITMI CEO John Niederhuber believes 

that the project will yield clues as to the 

genetic basis of premature births, and 

potentially even therapeutic targets for 

various obstetrical abnormalities. 

ITMI is a not-for-profit research institute 

within the Inova Health System in 

Northern Virginia. Niederhuber joined 

ITMI one year ago following his tenure as 

director of the National Cancer Institute 

(NCI). In that role, Niederhuber had 

already immersed himself in the potential 

medical benefits of next-generation 

sequencing (NGS). He launched a pilot 

program of The Cancer Genome Atlas 

(TCGA) with Francis Collins, director at 

the National Human Genome Research 

Institute at the time. 

Next-Gen Medicine 

“When I left the government last July 

[2010], I was wondering what could I 

do next?” Niederhuber says. “If we all 

believe the future of medicine is going to 

be transformed by this type of technology 

and others including proteomics, then 

maybe I could have some impact by working 

out how one is going to use this? Not 

just for research but making a difference 

at the point of care.” 

Niederhuber’s initial focus was on can- 


cer and other adult diseases, but he concluded 

that he would be echoing efforts 

going on elsewhere. On the other hand, he 

realized that Inova served a huge population 

of patients, with dozens of babies 

delivered every day, not to mention one 

of the largest regional neonatal intensive 

units (NICUs) at Inova Fairfax Hospital. 

“Maybe the future of medicine is about 

being able to do this care characterization 

before birth or at birth and build from 

there, understanding the potential targets 

for managing risk and having a reference 

point if disease develops down the road. 

That’s really next-gen medicine! We know 

very little about the causes of obstetrical 

diseases. We have no clue at all about 

what causes preterm delivery,” he says. 

Niederhuber received backing from 

his colleagues, including Inova CEO Knox 

Singleton. “They said, ‘No, you’re not 

crazy!’” Although he wondered if physicians 

and patients would be receptive, 

the ITMI proposal sailed through IRB 

approval. 

ITMI plans to sequence 250 pre-term 

babies with no known congenital abnormalities 

and 250 full-term newborns, 

along with their parents, for a total of 

1,500 genomes. ITMI has been recruiting 

families since last June, with more than 

150 entered to date. The first group of 

samples has already been sent to Com- 

plete Genomics for sequencing. 

Niederhuber says he had a lot 

of confidence in Complete Genomics 

“because of our past work 

at NCI”. He considered BGI as a 

potential outsourcing partner, but 

didn’t talk to the Chinese institute 

about this specific project. “That 

was because of its pilot nature, and 

I suppose I wanted more control 

and accessibility,” he says. 

The initial goal for Niederhuber 

and his collaborators is “to 

mine that data and find markers 

for pre-term delivery.” But that will raise 

many more questions: “How are we going 

to integrate this information with the 

phenotypic information of patient care? 

How are we going to make that useful 

information at the point-of-care with the 

physician, who may not know much about 

genetics?” 

A huge challenge will be the medical 

interpretation on the sequences. Niederhuber 

says that “conversations with a 

variety of entities” are taking place, with 

the goal of developing new interpretation 

tools, either in-house or in conjunction 

with others. “We will work with our own 

people, but we’ll also contract with others 

in partnership to apply the tools that 

exist. We’re very committed to trying not 

only to work on the data itself but also 

develop the tools to fill that space on the 

analytics side for patient care.” 

The next phase of the program will 

include a longitudinal cohort of 2,000 

offspring and is being finalized currently. 

Niederhuber outlined some of the likely 

areas of investigation: “What if we go to 

the obstetrics arena in the first trimester, 

and we consent the mothers, and look at 

proteins, genetics and so on, and follow 

through pregnancy? What if we followed 

after birth? What if we expand beyond 

parents into grandparents? That would 

be interesting.” •

Genia’s Nanopore/Microchip Technology 

Gains Life Technologies’ Support 

4th-generation sequencing 

platform taking shape in 

Silicon Valley. 


SAN FRANCISCO—The genesis of 

Genia, a promising Silicon Valley nanopore 

sequencing start-up, took place—not 

for the first time—with a serendipitous 

meeting at a popular branch of Starbucks 

in Menlo Park, California. 

Roger Chen was reading a book on the 

origins of life. Stefan Roever was buying 

a cappuccino. The two men struck up a 

conversation. Chen said he was developing 

a DNA sequencing machine in his 

garage, to which Roever replied, “What’s 

that?!” 

But it wasn’t long before Roever, a serial 

entrepreneur, was offering to help assemble 

a team and write a business plan. 

He recruited a couple of additional angel 

investors and signed on as CEO. 

“If Ion Torrent—electrical detection 

but requiring amplification—and Pacific 

Biosciences—single-molecule but optical—are 

3rd generation [sequencing 

technologies], then we’re 4th generation: 

single molecule, electrical detection,” 

says Roever. “That’s the holy 

grail, because it combines 

low-cost instruments with 

simple sample prep. So we’d 

like to think of it as last-gen!” 

Genia has since caught 

the attention of the big guns. 

In April 2011, Genia closed 

a strategic investment with 

Life Technologies that Dietrich 

Stephan, who sits on 

Genia’s scientific advisory 

board, calls “a double digit” 

[millions of dollars] investment. 

“Life is putting signifi- 

Roger Chen 

cant additional in-house resources behind 

the product,” he says. 

A Life Technologies spokesperson reserved 

comment on the investment. 

Genia is building an integrated circuit and says sequencing is just one potential application. 

“Genia is an amazing technology,” 

Stephan told Bio•IT World. “They have 

developed key proprietary innovations 

around the pore that allow single molecules 

of single-stranded DNA to move 

through the pore slowly, so the sequence 

can be measured accurately. Key innovations 

around the array-based sensor 

allow the pores to be electronically selfassembled 

into lipid films, and the DNA 

molecules to be moved bidirectionally 

under tight control.” 

Stephan continued: “The sensor itself 

is truly transformative and allows very 

small signals to be seen high above the 

noise floor, which is one 

of the issues all the other 

nanopore companies are 

struggling with, as well as 

allowing massively parallel 

measurements to be made 

directly on an integrated 

circuit.” 

Founding Four 

Roever moved to California 

in 2000 after building an 

Internet banking company 

in his native Germany in the 

late ’90s, which he took public 

and grew to 2,000 people. He has since 

been involved with various technology 

start-ups, although he admits he’s neither 

a biology guy nor an electrical engineer. 

“Right now, we’re more focused on building 

a product. Technology development is 

what I’ve done all my life,” he says. 

The name “Genia” was actually one of 

dozens of unused candidates that Roever 

received in an earlier naming study for a 

previous company that cost him $50,000. 

“I dug out that list and one of them stuck. 

Sounds like a good name for a sequencing 

company!” 

Stephan believes that one of Genia’s 

key differentiators is that most of the 

firm’s senior management has roots 

in the semiconductor industry. Chen 

(chief technology officer) and the other 

co-founders, Pratima Rao (VP marketing) 

and Randy Davis (VP R&D), are all 

alums of Maxim Integrated Products, 

one of the leading analog-to-digital chip 

companies, who gravitated independently 

to biochemistry. Chen worked with David 

Deamer in nanopore sequencing at the 

University of California Santa Cruz. Davis 

managed the UCSF cancer center core 

lab, and Rao previously headed product 

marketing for Affymetrix. 

In addition to Stephan, the scientific 

advisory board includes George Church 

(Harvard Medical School), and two of 

Stephan’s former Navigenics colleagues, 

Sean George (CEO Locus Development) 

and computational biologist Eran Halperin. 

They are joined by Bob Dobkin, 

founder of Linear Technology. 


CONTENTS

CONTENTS 

Next-Gen Data 

Analog Advantage 

A number of companies are vying to 

commercialize nanopore sequencing 

technology, including Oxford Nanopore 

in the UK, NABsys in Providence, RI, and 

NobleGen. So what does Roever consider 

is Genia’s advantage? 

“At our core, we’re an electronics 

platform,” says Roever. “We’ve got some 

developments on biochemistry, but we’re 

developing a massively parallel analog 

sensor to do nanopore-based sequencing, 

supporting a variety of chemistries on the 

[chip] surface. But at the core, we’re a 

chip company.” 

“Most chips today are purely digital— 

digital input, digital output, with some 

processing in the middle,” Roever continues. 

“A few chips take analog inputs, e.g. 

temperature sensors or a mobile phone 

sensor. It’s a bit of a black art.” 

Chen previously showed that by using 

custom electronics—state-of-the-art 

analog-to-digital processing with very 

small currents (picoamp range) and signal 

(femtoamp range)—it is possible to 

count “literally hundreds of electrons,” 

potentially a much finer resolution than 

competing technologies. 

A popular model in a nanopore sequencing 

scheme is to measure a single 

molecule of DNA traversing the pore. 

“The single base difference you’re looking 

for is effectively about 10 atoms,” says 

Roever. Those 10 atoms can be detected 

by measuring the electronic stream. “The 

signal is in the hundreds of electrons. 

You’re looking at the very edge of what’s 

electrically detectable.” 

While other companies are engineering 

genetically modified pores, Genia is 

building an integrated circuit—essentially 

a checkerboard array of analog-to-digital 

sensors or electrodes exposed on the chip 

surface. Each electrode is a few microns 

in diameter, potentially enabling as many 

as 1 million electrodes to be packed onto a 

chip. The analog-to-digital signal conversion 

occurs on the chip. 

The process sounds deceptively simple: 

put the DNA in solution above the array of 

nanopores and sensors. “We can make it 

all electronically—setting up the bilayer 

and the pore, plug the chip in, power it 

on to make the bilayers and pores,” says 

Roever. Next, apply the potential such that 


‘ We’re 

developing a massively 

parallel analog sensor to do 

nanopore-based sequencing, 

supporting a variety of chemistries 

on the [chip] surface.” 

current flows through the pores. “We detect 

the operating cells and start sucking 

in the DNA and measuring it… Sequencing 

is just one application. For example, 

you could put transporter proteins in the 

bilayer for drug discovery applications.” 

There are two advantages to this system, 

says Roever. “First, we can resolve 

signal much better than if you have to take 

signal off and process it outside. It’s easier 

for us to see single base differences. We 

can react to any changes by moving the 

DNA back and forth across the pore.” 

“Second, we can dynamically build 

these lipid bilayer/nanopore complexes on 

the chip surface. Instead of doing that mechanically, 

we’ve got software to make the 

bilayer and start the nanopore... Instead 

of a single sensor or a few hundred or a 

thousand, we have hundreds of thousands 

or 1 million.” 

Slow Motion 

The knock on nanopores has been the 

need to hinder the passage of singlestranded 

DNA through the pore. “We’ve 

got a way to slow it down, by a combination 

of electronics and some biochemistry,” 

says Roever. The current platform 

requires less than 2 seconds to read a base, 

but Roever expects to push that down to 

less than 1 second/base. “There could be 

1 million sensors at 1 base/second,” says 

Roever. 

Roever says Genia can actively control 

the DNA template, moving it back-andforth 

through the nanopore if required 

in a kind of flossing action. “We can 

oversample, rewind and read again. You 

change the applied voltage and the DNA 

goes backward. If you capture the DNA in 

the pore, you can ‘dental floss’ it—you can 

Stefan Roever, Genia 

read it 10-20 times.” Roever would not 

detail the read-out mechanism, other than 

to say, “Our approach relies on some IT to 

reassemble those sequences.” 

The chips themselves, he says, will 

be extremely affordable and have a cost 

structure similar to a standard semiconductor 

chip today. Patents have been filed, 

says Roever, who adds: “What we have 

to license will depend on what chemistry 

we decide to use, what pore we use, what 

technique we wind up doing... But for the 

core approach, we think we have freedom 

to operate.” 

One of the next goals for Genia is to 

build an instrument, which Roever says 

shouldn’t be any more elaborate than Ion 

Torrent’s Personal Genome Machine. “Ultimately, 

it could be a chip in a handheld 

reader connected to a PC,” he says. A milestone 

early next year will be receipt of the 

first working chip, containing hundreds of 

sensors, from a Taiwanese foundry. 

Roever says Genia is essentially “a platform 

to let nature do its thing.” He plays 

down talk of competition. “I don’t see Oxford 

Nanopore as a competitor—there’s no 

reason their chemistry couldn’t run on our 

platform, right? If they develop a working 

chemistry, get a better mutated pore, why 

couldn’t they run on our platform?” 

The Genia website dares to proclaim 

“the $100 genome.” Roever checks himself, 

but will say this: “Within the next 

decade, you’ll go to the doctor, the nurse 

will take a saliva sample and sequence 

everything in there. By the time you see 

the doctor, he’ll say it’s just a rhinovirus or 

Epstein-Barr virus or what have you. Instead 

of the guessing game today, people 

will look back to this time as medieval 

medicine!” •

IT/Workflow 

Making Semantic Sense of 

Unstructured Data 

Sophia’s Digital Librarian software relates documents without taxonomies. 


A 

somewhat stifling aspect of many 

sophisticated semantic search 

tools is the need to build ontologies 

and taxonomies to organize 

the data. Nonsense, says David Patterson, 

the co-founder and CEO of Sophia 

Search, who believes in freedom from 

taxonomies or ontologies. 

“People are so attuned to building 

taxonomies and ontologies because they 

think they need to,” says the Northern 

Irishman. “Our message is, that just isn’t 

true! We understand the purpose they 

serve, but one of our long-term goals has 

been to build a search tool that doesn’t 

rely on background knowledge structures. 

Let’s free people up from the overheads 

and expense of these knowledge 

structures.” 

The Sophia Digital Librarian search 

tool thrives on finding relationships between 

documents without the need for 

any kind of taxonomy. Just set the software 

loose on a collection of unstructured 

data, and it does the rest. 

Patterson co-founded Sophia with 

Vladimir Dobrynin, a professor at St. 

Petersburg State University and Sophia’s 

chief science officer. Patterson’s background 

is in artificial intelligence. He was 

director of an artificial intelligence R&D 

lab at the University of Ulster, working on 

data mining, machine learning, and information 

retrieval. Patterson has collaborated 

with Dobrynin since 2003. After 

some five years of R&D, the researchers 

came up with a prototype version of Sophia. 

The Sophia product engineering 

team is based in Belfast, while the R&D 

team is based in St. Petersburg, Russia 

and sales in Silicon Valley, California. 

Semantic Searching 

“The Sophia Digital Librarian is all about 

content enrichment within organizations 

or repositories,” says Patterson. “It helps 

organizations improve the findability of 

the content they have in their organization 

or external repositories.” Interest 

is high among pharma companies, life 

science organizations and the scientific 

publishing community. 

The Digital Librarian is built on Sophia’s 

patented contextual discovery engine,” 

says Patterson. “We’re empowering 

organizations to become more innovative 

and creative through discovery. Search 

should not just be about retrieving information 

you expect to find but also about 

uncovering and discovering new things 

you weren’t aware of.” 

Taxonomies can stifle 

innovation, says Patterson, 

by constraining 

staff to all think 

conventionally and 

uniformly. “You’re not 

allowing your employees 

to think freely… If 

we are constrained by 

the boundaries of conventional 

thinking, we 

limit creativity and our 

ability to discover new 

things. Sophia removes 

these constraints and 

David Patterson 

enables users to discover unknown relationships 

and knowledge from within 

their content—that’s the real power behind 

what we do.” 

After reading through documents in 

an organization’s repository, the Sophia 

Librarian gets to work. “It extracts the 

meaning, organizes them into topics, 

understands what they’re about, captures 

metadata describing their topic and 

subtopics, and attaches tags to the document 

to make them more findable,” says 

Patterson. Tags can be extracted from 

the document, but the tool also creates 

semantic tags—relevant words or phrases 

that do not actually crop up in the source 

document. 

“We also identify the most similar 

documents among all the documents 

in the corpus,” says Patterson. “Then we 

rank the “nearest neighbors”—the most 

semantically similar documents. This 

quickly brings to the user a list of related 

documents and helps users focus and find 

information relevant to their needs.” 

The metadata—Sophia calls it the 

“semantic profile”—are exposed as XML, 

through a series of web services to make 

the information available to any search or 

content management tool. The goal, says 

Patterson, is to augment 

current search tools and 

make them smart. 

In a quick demo, Patterson 

uses Sophia to automatically 

create a semantic 

profile for a document 

taken from the Web using 

knowledge extracted 

from a corpus of 1.8 million 

news stories spanning 

20 years. The articles 

have been automatically 

indexed by Sophia and 

semantic profiles created 

for each document. “Sophia 

uses knowledge extracted from these 

documents to come up with a semantic 

profile—topic, tags and nearest neighbors—for 

the new document,” he says. It 

uses knowledge extracted from the news 

corpus to intelligently assign metadata to 

the new document. 

A similar search can be done using an 

abstract from PubMed on Alzheimer’s 

disease, for example, retrieving tags related 

to dementia, amyloid protein, and 

neurodegenerative diseases among others. 

The numerical score offers a gauge 

of the “distance” between the source 

document and any retrieved article. “Our 


CONTENTS

CONTENTS 

IT/Workflow 

capabilities relate topics and documents 

together that wouldn’t have been otherwise 

known,” says Patterson. “We’re able 

to make connections years ahead of [traditional 

means of] discovery.” 

In time, it will be possible to filter 

those results by source or date, for example 

selecting just PDFs or documents 

within a specific date range. The functionality 

is there, says Patterson, it just requires 

using a web services user interface. 

Customer Stories 

Sophia’s sales director Jeff Bierach says 

the company has a number of customers 

in the U.S. already, and is targeting many 

more in the life sciences community and 

publishing sectors. As discussed in a 

recent Bio•IT World guest commentary 

(see, “Reevaluating the Role of Research 

Librarian in Pharma R&D,” Bio•IT World, 

Sept 2011), many pharma companies have 

been downsizing their librarian staff for 

some time. 

“Look at what’s been happening in 

pharma companies over the last 3-5 

years,” says Bierach. “Genentech used 

to have a staff of over 20 librarians—researchers 

finding information. They have 

zero now. That’s really a big play for us, to 

automate a lot of this capability around 

discovery and document classification. 

Those are really time consuming tasks 

that we can automate.” 

One big pharma company had spent 

three man-years building custom queries 

for PubMed to extract information 

on over 30 different topics they track. 

“Based on the last two years of MED- 

LINE abstracts which we have indexed, 

our client was able to reproduce those 

queries in Sophia in less than one week,” 

says Bierach. “We essentially solved his 

entire job that took three years to get to 

where he is now. There’s a huge amount 

of value there. 

“We’re starting to create semantic profiles 

for content of a pharma company in 

San Francisco,” adds Patterson. “They use 

Microsoft FAST [search tool] and want 

to add semantic profiles to the content.” 

With stagnant drug discovery pipelines, 

Patterson also sees an opportunity in drug 

repositioning, helping to find correlations 

at significant cost savings. 

While most content search applica- 


A search done using a PubMed abstract on Alzheimer’s disease retrieves related tags, and the 

estimates the “distance” between the source document and any retrieved article. 

tions focus on bespoke internal datasets 

rather than the web, Patterson says 

Sophia is looking to work with partners, 

including a Google reseller in Chicago. 

“We’ll supply a layer between the Google 

search appliance and Sophia.” 

Another promising target segment is 

the publishing sector, which could leverage 

Sophia to ‘up-sell’ related journal articles 

to customers. Another early project 

involved helping a publishing company 

sift through 20 years of legacy content. 

“Within three days, we were able to see 

what information was evergreen. The client 

said that saved him 9 man-months of 

effort,” says Patterson. 

Version 1.2 of the Sophia Digital Librarian 

is now in full commercial release, 

but Patterson stresses that his team is still 

building functionality. Because the company 

is relatively small, “we can move very 

quickly,” says Bierach. •

The PAREXEL Biopharmaceutical R&D Statistical 

Sourcebook 2011/2012 is the leading resource for statistics, 

trends, and proprietary market intelligence and analysis on 

the biopharmaceutical industry. Supported by thousands 

of graphs, illustrations, and analysis, the Sourcebook 

provides the latest intelligence on every aspect of 

biopharmaceutical development – from product discovery, 

to R&D performance and productivity, to time-to-market 

trends. 

With key analysis and contributions from leading 

consultancies and experts, the Sourcebook provides 

real-world data and analysis, including: 

• New proprietary analysis on US clinical trial starts, 

segmented by therapeutic category, as well as overall active 

clinical trials 

• Emerging data on worldwide and company-specific R&D 

pipelines and product launch trends 

• An all-new and comprehensive analysis of clinical research 

off-shoring revealing which pharma companies are now 

locating their new clinical trials overseas 

• New analysis on emerging trends in pharma and biotech 

licensing deals and other partnerships critical to industry’s 

efforts 

• Drug approval statistics compiled from FDA, EMA, and other 

regulatory agencies 

• New global R&D spending trends and other 

international R&D data from key markets 

• International statistics on drug 

development output 

• And much more! 

Plus, NEW in the 

2011/2012 edition: 

• All-new analyses and actual/ 

projected metrics on the 

biosimilars market 

• A series of new 

“dashboards” on costs 

by phase of development, 

R&D attrition rates, product 

development times, and 

other areas 

• Forecasting models on 

biopharma sales, R&D 

spending, the pharma/ 

biotech markets, and other 

meaningful industry metrics 

• New analyses on patient 

recruitment into clinical trials 

The PAREXEL Biopharmaceutical 

R&D Statistical 

Sourcebook 2011/2012 is a 

must-have resource for the 

drug development industry. 

It is an invaluable resource 

for executives and managers 

working in the pharma 

and biotech industries. The 

Sourcebook puts real-world 

data sets at your fingertips 

for presentations, reports, 

business development efforts, 

strategic meetings, and critical 

decision-making analyses. 

The 2011/2012 edition will once 

again be offered in electronic 

format for individual users, 

small groups, business units, 

or for company-wide access. 

To reserve the PAREXEL 

Biopharmaceutical R&D 

Statistical Sourcebook 

2011/2012, call 1-800-856-2556 

or email customer.service@ 

BarnettInternational.com/ 

Publications.

CONTENTS 

IT/Workflow 

The British Are Coming, 

Connecting People and Patients 

BT Global Services’ Yury Rozenman discusses the 

changing landscape of pharma services. 


Why would a chemist who has worked 

for some of the leading bio-IT companies 

of the 15-20 years, including Celera Genomics, 

Applied Biosystems, D.E. Shaw 

Ventures and IBM, find himself working 

for the company formerly known as British 

Telecom? 

“I was just as surprised,” said 

Yury Rozenman, who is BT Global 

Services’ head of marketing strategy 

and solution development for 

life sciences (see, “A Long Road to 

BT”). “Why would BT Global Services 

be interested in developing 

solutions for pharma?” 

Why, indeed. At the time, he 

explained, BT began to realize 

that, even as companies such as 

IBM present solutions for data 

integration and connectivity, “the 

missing element was connecting 

people, making sure they could 

make sense of the information 

and bring greater value to pharma 

companies.” 

One of the most exciting examples 

of enterprise communications 

services offered by BT Global Services 

is the management of all patient 

records for the UK’s National 

Health Service (NHS), including 

solutions such as e-prescriptions 

and pharmacovigilance. “We knew 

we could take those assets and 

apply them globally to the health 

care and life sciences ecosystem— 

pharma, biotech, CROs, and potentially 

even payors and providers,” says 

Rozenman. 

BT’s bread and butter is in what 

Rozenman calls “transformational deals,” 

where pharma companies acknowledge 

that tasks such as managing a global network 

is not their core expertise. BT wins 

if it can demonstrate it can bring better 



return on investment and implement useful 

services on top of the network—and do 

it all, of course, in accordance with tight 

regulatory requirements (e.g. GxP, FDA 

21 CFR Part 11, etc). 

In 2005, BT signed a large US pharma 

to manage its enterprise communications 

Yury Rozenman heads BT’s market strategy for life sciences. 

services, as well as Swiss and Japanese 

companies. “But it’s always difficult to get 

public release,” Rozenman sighs, unable 

to divulge the client’s name. 

“Most of our clients are multinational 

corporations,” says Rozenman. “We connect 

people around the world with data/ 

voice applications. For the most part 

we try to focus on companies that need 

global reach to support their internal and 

external operations. We work with the 

top 25-30 pharma companies, as well as 

CROs and medium-sized biotechs.” 

A large percentage of BT’s core services 

fall around strategic outsourcing— 

largely LAN/WAN security and unified 

communications. “That’s how we start 

usually. That’s our way in,” says Rozenman. 

“We need to prove we can do that 

well. We work with HP, Dell, EDS, 

IBM, it depends—the pharma 

company will carve up their IT 

outsourcing operations into towers, 

so servers/storage might go 

to IBM, communications to BT, 

laptops to HP, [consulting] to Accenture… 

We have to work across 

all the vendors.” 

More Than Core 

In recent years, however, BT has 

been hearing from customers 

that supplying core services isn’t 

necessarily sufficient. Paraphrasing, 

Rozenman hears things like: 

“You have expertise, but this is 

not enough. For us to continue to 

work with BT, you need to provide 

solutions not just for cost containment, 

but start creating more 

value, a balance between cost and 

payment.” 

“We work with pharma to 

identify what they want us to support. 

That usually differentiates us 

in terms of price and capabilities 

from other telecoms,” says Rozenman. 

Those needs increasingly 

include the ability to handle large 

data volumes and ensure they can 

travel around the world securely. And 

there are specific areas around R&D collaboration, 

chronic disease management, 

patient compliance, and the supply chain. 

One of those projects, with Liverpool 

City Council, is a “home of the future” 

pilot to study the management of chronic 

diseases for the elderly population. This

pilot focused on supporting patients in 

their home environment, using sensors 

and a self-learning system to learn about 

the patient’s behavior and detect signs of 

trouble such as a fall in the home, lack of 

movement, etc. 

On the supply chain side, Rozenman’s 

team is helping track, trace and authenticate 

drug supplies, in some cases down 

to a specific bottle, in an effort to combat 

rampant counterfeiting of approved 

drugs, identifying “grey markets” and 

potentially initiating drug recalls. 

Support of patient compliance, persistence 

and adherence to dosing during 

clinical trials (and approved drugs) is 

another key area for BT solution development. 

Even highly successful and effective 

drugs such as Gleevec show non-compliance 

rates around 30 percent. “If there is a 

drop in compliance, the pharma sponsor 

will allocate more drug to drive compliance. 

We need an intervention mechanism,” 

says Rozenman. “It’s not about 

reminders. It’s about the ability to connect 

the patient to the doctor, providing 

the necessary support mechanism, and in 

cases of adverse effects, providing patient 

training and options to help patients alleviate 

symptoms,” says Rozenman. 

Cloud Sourcing 

BT has great interest in cloud computing 

applications, recently running a “hothouse” 

event in London to bring stakeholders 

together. “There is significant 

interest from pharma around private 

clouds or hybrid clouds, not public,” 

says Rozenman. “Having said that, we’re 

running a very large cloud service for financial 

firms, called Radianz. It connects 

trading floor operations, content services, 

and transactional operations. We’re in the 

process of developing something similar 

for pharma.” 

“We have not launched the platform in 

the full sense yet,” says Rozenman, but the 

company has run pilots for a UK pharma 

and seen some ideas incorporated into the 

Pistoia Alliance. It is also working with 

the MIT Media Lab and the BioTeam, as 

well as a large ISV “to become a foundational 

partner in the ecosystem… running 

apps in the BT Cloud environment.” 

The needs of financial services and life 

sciences are very different, however. The 

A Long Road to BT 

Yury Rozenman has spent most of his career in the life sciences and pharma since 

graduating from the University of Illinois 25 years ago. A chemist by training, he 

worked for GD Searle in Chicago (now part of Pfizer), running analytical development 

before switching to licensing and acquisitions, searching for new compounds 

to bring into the pipeline. 

In 1993, he joined Applied Biosystems, helping develop DNA sequencing and 

genotyping technologies. When ABI launched a sister company, Celera Genomics, 

in 1998, Rozenman worked for Craig Venter and colleagues in field operations, 

interfacing with pharma companies seeking access to gene databases, advising on 

IT infrastructure. 

Rozenman later went to work for D.E. Shaw Ventures, which started among 

others Amazon, Schrodinger, and an online service called Juno (which merged with 

NetZero in 2001) for computational analysis. Following stints with Platform Computing 

and IBM, where he worked with Carol Kovac, again focusing on industry 

solutions for pharma, he joined BT Global Services. K.D. 

key attribute for financial firms is very 

low latency. “It’s not necessarily compute 

intensive, but very network centric. They 

have to move data, provide security, and 

encryption.” 

Pharma, by contrast, typically doesn’t 

run a single app but data pipelines, and 

thus requires many data sources around 

the world to be connected. “It’s not Windows 

but Linux or UNIX, so you need 

multiple platforms. And if you’re running 

a pipeline, you are running different programs. 

If it is clinical data, you may not be 

able to move data due to EU regulations 

(privacy protection laws). Everything we 

can do in the financial cloud we’ll take to 

apply [to pharma].” 

Rozenman says BT Global Services 

hopes to help ISVs deliver on demand 

services. By 2014, pharma says it wants to 

externalize their R&D or clinical services. 

“Within six months, we’ll have some proof 

of concepts completed and additional 

requirements to launch Phase 2. We want 

an app store, but we’re discussing with 

Schrodinger, Eagle Genomics and others… 

how to increase the use of in silico 

biology and chemistry through cloudbased 

services.” 

BT is in the business of “business enabling,” 

says Rozenman, and prefers to 

build solutions around the clients’ needs 

rather than create its own software. “We 

need to calculate: is it cheaper to move 

data to the app or stage the app in a 

virtual data center around the world? 

Depending on the requirement, data 

size, and resources, we can make decision 

automatically whether we stage or move. 

There’s enough intelligence in our cloud 

that we can stage very quickly.” 

BT Global Services has its own security 

group that develops solutions for 

pharma and other industries. “We look at 

regulations, how infrastructure needs to 

be rolled out depending on the vertical. 

HIPPA rules to anonymize data if you 

need to.” 

“Perception is important,” says Rozenman. 

“We can enforce rules, privatize data 

and IP, or share with single clients. We 

can create rules to ensure that is in place. 

We’ll also do ethical hacking if they want 

us… to try to break the security.” 

While clinical endpoints are classical 

data points, Rozenman says BT’s system 

is capable of taking genotype/phenotype 

information. “As we move forward in 

diagnostics, with complete genomes, you 

can reliably use the information to pick 

the right people for clinical trials, and 

quickly do genotyping, identify the right 

cohorts… Instead of 3,000 patients, you 

can get away with smaller, more focused 

clinical trials. We’d like to use our R&D 

platform to support early research informatics 

and simulated clinical trials. 

We’re in discussions in software around 

simulating clinical trials, to structure protocols 

and run more efficient trials. This is 

a very interesting area for our health care 

practice.” • 


CONTENTS

CONTENTS 

Free Trials & Downloads 

Company: Brainloop 

Product: Brainloop Secure Dataroom 

Description: Brainloop offers a highly 

secure online workspace for drug partnering 

plus collaboration on clinical trials, 

regulatory filings, manufacturing. 

Fast setup and prevent printing, forwarding, 

saving. 

Try it for free: http://bit.ly/FreeBrainloop 

Company: Real Time Genomics 

Product: RTG Investigator 

Description: Real Time Genomics offers 

RTG Investigator sequence analysis software 

to approved biological investigators 

with a renewable individual license good 

for 12 months. 

BioBASE Try it for free: http://bit.ly/FreeRTG 

Company: BIOBASE 

Products: TRANSFAC and ExPlain 

Description: TRANSFAC contains data on 

eukaryotic transcription factors, their 

binding sites, and regulated genes. 

ExPlain is a companion data analysis 

system that combines promoter and 

pathway analysis tools. 

Try for free: http://bit.ly/FreeBiobase 


Company: Enlis Genomics 

Product: Enlis Genome Research Edition 

Description: Enlis offers a genomic analysis 

tool for academic and industry 

researchers. The software enables analysis 

and visualization of genomic 

sequence data with unparalleled clarity. 

Try it for free: http://bit.ly/FreeEnlis 

Company: goBalto 

Product: goBalto Tracker 

Description: The easiest way to start your 

clinical trial on the web: Introducing 

goBalto Tracker the fastest way to get 

your investigators up and running. 

Try it for free: http://bit.ly/FreeGoBalto 

Company: CLC bio 

Products: CLC Genomics Workbench 

Description: CLC Genomics Workbench, 

for analyzing and visualizing Next Generation 

Sequencing data, incorporates cutting-edge 

technology and algorithms, 

while also supporting and integrating 

with the rest of your typical NGS workflow. 

Try it for free: http://bit.ly/FreeCLCbio 

Feature Your Free Download 

To have your free trial or download listed on this page, contact 

Allison Proffitt, Managing Editor at aproffitt@healthtech.com 

Ask a question or Cut n’ Paste//Results 

Statins have demonstrated their 

anti‐apoptotic effects by blocking A‐ 

beta 1‐42 induced neuronal death. 

Statins modulate the expression of 

molecules … 

Do statins have 

an effect on Akt 

phosphorylation? 

Open at the exact 

Page . . . 

Open at the exact 

Paragraph! 

Company: Praxeon 

Product: Document Lens 

Description: See firsthand how DocumentLens 

can help you organize your 

scientific articles, focus on the knowledge 

contained within, and enhance 

collaboration between groups. 

Try it for free: http://bit.ly/FreePraxeon 

Company: Omixon 

Product: Omixon Letter Space Toolkit 

Description: Find insertions and deletions 

1

New Products 

Watch a video about 

the BaseSpace Cloud 

Platform for MiSeq. 

Illumina’s Benchtop Sequencer 

Illumina’s much anticipated 

benchtop next-generation sequencing 

(NGS) instrument, the MiSeq, 

is shipping now and is available 

with a series of enhancements 

including streamlined sample processing 

and a new Cloud platform 

called BaseSpace that supports the 

platform. (see, “Illumina Launches 

BaseSpace Cloud Platform for 

MiSeq”) The goal of the new Base- 

Space Cloud platform is to provide 

a seamless pathway to get genomics 

data to the Cloud, expand on 

the space, and provide different 

types of analysis tools. The Cloud 

Updated Data Integration 

IO Informatics has released Knowledge Explorer, 

version 3.6, a tool that makes it possible for informaticians, 

data analysts and integration experts to integrate 

data with truly unmatched ease and efficiency. 

Enhancements and improvements make it easier 

for researchers to discover models, signatures and 

profiles by uncovering actionable meaning from their 

data and by contextualizing complex relationships for 

concise visual comprehension. 

Product: Knowledge Explorer v3.6 

Company: IO Informatics 

For more information: www.io-informatics.com 

platform is deployed using Amazon 

EC2. “The addition of BaseSpace 

eliminates the need for expensive 

IT infrastructure, simplifying the 

process of adopting a personal 

sequencer for labs of any size and 

experience,” commented Illumina 

CEO Jay Flatley. 

The MiSeq runtime is 27 hours 

for a 2x150-basepair run, for a total 

throughput of 1.7 Gigabases. The 

instrument retails for $125,000. 

Product: MiSeq 

Company: Illumina 


www.illumina.com 

Data Collection on the Web 

Oracle has announced the release of OutcomeLogix 

On Demand 3.0, a Web-based, 

scalable data collection system that enables 

life science companies and contract research 

organizations (CROs) to capture therapy 

outcome information from health care 

providers and patients in late-stage studies. 

The new version incorporates several features 

to help meet increasing requirements 

to improve product safety and demonstrate 

long-term treatment efficacy: increased 

scalability, improved user interface, updated 

prompting tools, enhanced configurability, 

and expanded multi-lingual support. 

Product: OutcomeLogix On Demand 3.0 

Company: Oracle 

For more information: www.oracle.com 

Image Analysis for 

Biomarker Discovery 

Definiens has released the company’s new 

Quantitative Digital Pathology portfolio, 

designed to advance translational research 

in pathology, specifically in biomarker 

development. The new portfolio will offer 

updated versions of Definiens Tissue Studio, 

Definiens Developer XD as well as the introduction 

of a novel component, Definiens 

Image Miner, which closely integrates data 

mining with image analysis to accelerate 

biomarker research. 

Product: Quantitative Digital Pathology 

portfolio 

Company: Definiens 

For more information: quantitative-digitalpathology.definiens.com 

Speedy Bioinformatics 

TimeLogic has announced the release of the next generation 

in Field Programmable Gate Array (FPGA) based DeCypher 

systems for biocomputing. The upcoming system, codenamed 

J1, will be released early next year with the equivalent performance 

of several thousand 3 Ghz processor cores in a single 1U 

server. Performance gains with the new system are expected to 

be tremendous. For example, Tera-BLAST, TimeLogic’s implementation 

of the popular BLAST algorithm, will run hundreds 

of times faster than the current generation of SeqCruncher bioinformatics 

accelerators and will allow a single 1U server, with 

accelerated BLAST, to replace a full rack of multi-core servers. 

Product: FPGA system codenamed J1 

Company: Active Motif 

For more information: www.timelogic.com 


CONTENTS

Educational Opportunities 

Keep abreast of the variety of educational events in the life science industry 

that will help you with your business and professional needs. To preview 

a more in-depth listing of educational offerings, visit the “Events” section 

of bio-itworld.com. 

To list an educational event, email lscimeme@healthtech.com. 

Featured Events 

CHI Events 

For more information on these 

conferences and other CHI events, 

visit healthtech.com. 

Biobanking: Maximizing Your Investment 

December 6-8, 2010 | Providence, RI 

The Compound Management Forum 

December 7-8, 2010 | Providence, RI 

Clinical Project Management Clinical 

Project Management 

December 8-9, 2010 | Philadelphia, PA 

January 9-13, 2012 | Coronado, CA 

High-Content Analysis 

January 10-13, 2012 | San Francisco, CA 

Live-Cell Imaging 

January 12-13, 2012 | San Francisco, CA 

Biomarker Assay Development 

January 31 - February 1, 2012 | San Diego, CA 

Barnett Educational Services 

Barnett Live Seminars 

Data Management in the Electronic Data 

Capture Arena 

December 1-2, 2011 | San Diego, CA 

Monitoring Clinical Drug Studies: 

Advanced 


Patient Registry Programs 


Drug Safety and Pharmacovigilance 

December 5-6, 2011 | Boston, MA 

Regulatory Intelligence 

December 7, 2011 | Philadelphia, PA 

Executive Summit West: Drug-Diagnostic 

Co-Development 

January 31 - February 1, 2012 | San Diego, CA 

Summit for Clinical Operations 

Executives (SCOPE) 

February 7-9, 2012 | Miami, FL 

Cloud Computing 

February 19-20, 2012 | San Francisco, CA 

Next Generation Pathology 



Integrated R&D Informatics for 

Knowledge Management 


Bioinformatics & Cancerinformatics 

2012 


March 5-8, 2012 | San Diego, CA 

microRNA in Human Disease and 

Development 

March 12-13, 2012 | Cambridge, MA 

font is Petita Bold 

Visit BarnettInternational.com for detailed information on Barnett’s live 

seminars, interactive web seminars, on-site training programs, customized eLearning 

development services and publications. 

Conducting Clinical Trials in Resource- 

Limited Settings 


Monitoring Clinical Drug Studies: 

Intermediate 


Medical Device GCP Overview 



Statistical Concepts for Non-Statisticians 


Working with CROs 


Pharmacovigilance Audit 

December 13, 2011 | San Diego, CA 

April 24-26, 2012 | Boston, MA 

PEGS: the essential protein engineering 

summit 

April 30 - May 4, 2012 | Boston, MA 

Strategic Alliance Management Congress 

May 7-9, 2012 | Philadelphia, PA 

Biomarker World Congress 

May 21-23, 2012 | Philadelphia, PA 

World Pharmaceutical Congress 

June 5-7, 2012 | Philadelphia, PA 

June 6-8, 2012 | Singapore 

Effectively Writing the Investigators 

Brochure 

December 14, 2011 | Philadelphia, PA 

Global IND Submissions 


Institutional Review Boards (IRBs) 


Barnett Web Seminars 

Introduction to Data Management 

December 5, 2011 

NEW! Implications of the New FDA 

Guideline for a Risk-Based Approach to 

Monitoring 


NEW! Disqualification of Clinical 

Investigators: Proposed Rule and FDA 

Transparency Initiative 


NEW! Electronic Source Documentation:

Webcasts, White Papers, and Podcasts 

Visit bio-itworld.com to browse our 

extensive list of complimentary Life 

Science white papers, podcasts and 

webcasts. 

To learn more about developing a 

multimedia lead generating 

solution, contact Lisa Scimemi at 

lscimemi@healthtech.com 

Whitepapers 

A BPM-Approach to Adverse Event 

Management 

Sponsored by Pegasystems 

Safety management is 

one of the most difficult 

requirements imposed 

on the life sciences 

industry. Companies 

confront a tangle of 

safety monitoring 

requirements that span 

both pre- and postmarket 

approval activi- 

By joHn russell 

ties and vary by IRB/IEC governance policies, 

product type, and different global regulatory 

agencies. Learn how Pegasystems BPM and its 

Adverse Event Case Processing Solution (AECP) 

can help companies: 

• Transform adverse event management systems 

• Lower cost with increased productivity 

One client successfully utilized Pega BPM to 

establish paperless adverse event reporting 

across 23 countries, resulting in upwards of a 

Navigating the New FDA Draft Guidance 


NEW! FDA’s Bioresearch Monitoring (BIMO) 

Program: New Guidance for Inspection of 

Sponsors, CROs, and Monitors 


NEW! Financial Disclosure: New FDA 

Draft Guidance for Clinical Investigator 

Reporting 


Drug Safety and Pharmacovigilance 


Site Management and the Art of 

Assertiveness 


A BPM-Approach to 

Safety Management 

Produced by Cambridge Healthtech 

Media Group Custom Publishing www.pega.com 

Monitoring Phase I Clinical Trials 


NEW! De-Risk Your Protocol by Developing 

an Operational Advisory Board 


100% increase in productivity with near 50% 

cost reduction. 

Visit: www.bio-itworld.com to download 

Accelerating Decision Making Processes in 

Life Sciences R&D 

Sponsored by HP and Microsoft 

Life sciences organizations need an easy way to 

access and share information to make timely 

R&D decisions. Read this white paper to learn: 

• How IT and business challenges complicate 

decision-making efforts 

• How to avoid missed opportunities, duplicate 

work, and inefficient use of time 

• How a jointly developed HP and Microsoft 

business intelligence appliance provides a 

way for life sciences researchers and managers 

to accelerate their analysis and decisionmaking 

work. 


Embedding Oracle Technologies in 

Life Sciences Solutions 

Sponsored by Oracle 

Data drives science, but can slow it down. If 

data-structured or unstructured- is made 

more easily accessible, more easily shared, 

and more readily analyzed it will produce better 

results. In life science and healthcare that 

can mean the difference between a new drug 

finding its way to the healthcare market and 

patient, or simply getting lost in the data glut. 

Oracle’s Embedded technologies can lower 

problematic data hurdles while producing 

innovation and productive outcomes. This 

paper discusses how Independent Software 

Vendors, Original Equipment Manufacturers 

and, of course, users can quickly and easily 

implement solutions that leverage Oracle 

embedded technologies. 

The paper covers benefits for both vendors 

and users including: 

• Vendor advantages: Faster time to market, 

greater differentiation, customer satisfaction, 

enterprise class support and security. 

• User advantages: Improved Data handling, 

faster clinical trials, improved business 

reporting, improved ROI. 


Podcast 

Metrics that Matter: How Actionable Data 

Can Drive Better Decisions 

With the widespread 

adoption of eClinical 

technology, clinical operations 

departments have 

access to unprecedented 

amounts of data. This 

podcast will discuss how 

clinical business analytics 

can help sponsors effectively mine that data to 

make more informed decisions. 

Industry executives will address the follow- 

ing questions: 

• What are the key technical and organizational 

challenges to efficiency in clinical 

operations? 

• How is the definition of actionable data 

evolving? 

• How can clinical business analytics be an 

agent of change for an organization? 

• What technical and organizational issues 

should sponsors consider when seeking a 

business analytics solution? 

Speakers: Stephen Young, Senior Product 

Director, Medidata Solutions and Laurie 

Halloran, CEO & President, Halloran Consulting 

Group 

Listen Now — Visit: www.bio-itworld.com to 

download 

For more details on this newly 

published report, visit 

InsightPharmaReports.com 

Web Symposia Series covers a broad array 

of topics within the life sciences and drug 

development enterprise. 

• Register for upcoming web symposia 

• Listen to recorded web events 

• Purchase a DVD or Electronic Version 

• Sponsor a symposium on a topic of 

your choice 

For details on the Web Symposia 

Series, visit www.bio-itworld 

symposia.com or email lscimemi@ 

healthtech.com 

www.bio-itworld.com NOVEMBER | DECEMBER 2011 BIO•IT WORLD [53]

CONTENTS 

The Russell Transcript 

Crescendo 

Bioscience’s 

Aspirations 

JOHN RUSSELL 

The rise of personalized medicine—however broadly 

or narrowly we define it—has been stymied in part 

by a lack of effective biomarkers. Cancer is perhaps 

an early and growing exception. The trend to profile 

a specific patient’s tumor for markers to help physicians 

pick the best therapeutic regime is a good example 

of the growing sophistication of biomarkers and their longterm 

potential as the cost of performing such tests declines. 

Of course many diseases could (and eventually will) benefit 

from the kind of biomarkers becoming common in cancer. Biomarkers 

are necessary linchpins to enable modern medicine to 

translate advances in understanding disease biology into practical 

diagnosis, prognosis, and treatment. One young company, 

Crescendo Bioscience, has set its sights on developing and commercializing 

markers for autoimmune diseases. It’s a ripe area 

and the investing community seems to agree. In September, 

Crescendo completed a $31 million Series C round and also 

struck a strategic investment deal with Myriad Genetics for 

$25 million. 

Crescendo’s first target is rheumatoid arthritis (RA). CEO 

William Hagstrom says, “It was interesting. You could walk 

around trade exhibits floors and see all manner of descriptions 

of RA biology and pathways and mechanisms of how drugs 

affected them. There wasn’t a single booth or company talking 

about how they were measuring those things so physicians 

could better understand what to do with these drugs.” 

RA is a solid target on two critical grounds. First, like a great 

many biomarkers, current RA markers are both coarse and almost 

entirely subjective. 

‘’You don’t cure RA and most autoimmune patients generally. 

You seek to put them into clinical remission and the standard 

measures for assessing inflammatory disease activity all had to 

do with external manipulation of patients joints or digits and 

doing calculations which were qualitative and subjective as opposed 

to being based the biology of the disease,” Hagstrom says. 

Second, there are around 3,500 office-based rheumatologists 

in the U.S. alone who treat patients with many different autoimmune 

diseases, and the typical RA patient has four visits each 


year. Marketing to that physician community and their patients 

is a doable task and a sizeable market. The chronic nature of the 

disease has also created an active patient community seeking to 

self-manage their disease and receptive to new approaches. 

Markers for Disease Biology 

The cornerstone of Crescendo’s approach is to develop quantitative 

markers based on detailed models of disease biology. 

Its first test—Vectra DA—launched last year at ACR is a blood 

test that measures 12 key proteins consistently associated with 

RA disease activity and integrates them into a single objective 

score for easy interpretation. 

The test is intended to provide physicians with a quantitative 

glimpse into RA activity and was developed much the way 

modern drugs are. Drawing from the literature and using computational 

tools such as Ingenuity Systems’ pathway database 

and analysis software and Entelos’ RA Physiolab platform, Crescendo 

built a detailed picture of RA biology. 

“We were technology agnostic at the front end and chose to 

screen very large numbers of biomarkers on several different 

technology platforms (e.g. gene expression) to determine which 

markers correlated [with] quantitative disease activity,” says 

Hagstrom. Of an initial list of 390 markers, Crescendo identified 

a small subset to take into a formal development program. 

“We optimized the biomarkers, 

put them on a single technology 

Listen to the audio podcast 

“Entrepreneurial Journeys in 

Healthcare” with William Hagstrom. 

platform, and built a cohort of 25 

centers across North America called 

INFORM, which was used as the 

William Hagstrom 

primary sample set for efforts to develop 

an algorithm able to deliver a quantitative score on a scale 

of 1 to 100 to discern a patient’s level of disease activity,” he says. 

Validation studies in Europe and the U.S. followed. Crescendo 

has a CLIA lab in San Francisco and is a member of the Batter 

Up consortium (see, “Batter Up: A Stratified Approach to 

Rheumatoid Arthritis,” Bio•IT World, March 2011) working on 

multiple approaches to RA treatment. 

Currently, Vectra DA is not linked to any specific therapeutic. 

“A physician can see in the face of various drug therapies 

whether the disease activity is declining, stable, or increasing. 

But we are not measuring drug effect, nor are we seeking to 

predict a drug response or a drug selection at this point in time. 

Those are targets of future product development activities,” 

Hagstrom says. Crescendo already reports the levels of the test’s 

constituent proteins. 

It will be interesting to track Crescendo’s progress and its 

impact on broader industry efforts to develop and commercialize 

biomarkers required to deliver personalized medicine.

10th Annual BioPartnering North America 

Growing Life Science 

Business in the Pacific Rim 

www.techvision.com/bpn 

10th Annual BioPartnering North America 

Vancouver Convention Centre | Vancouver, BC, Canada 

26-28 February 2012 

Now in its 10th year of success, BioPartnering North America will build on 

strong relationships focusing more clearly on the Pacific Rim. Vancouver is 

well placed to provide these crossroads, where companies from around the 

world can access new business opportunities. With strong support from trade 

associations in Asia, Europe, North America, and elsewhere, together with 

creative input from our Advisory Boards, we are planning to take BPN to a 

higher level, and this year’s theme indicates this shift in emphasis: 

Growing Life Science Business in the Pacific Rim. 

PRODUCED BY: POWERED BY: HOSTED BY:

Life Sciences 

Innovation Forum 

Harness Innovation in a Shifting Global Business Climate 

January 26-27, 2012 Marriott Forrestal Village Conference Center, Princeton, NJ 

Featuring Insights into the Latest Innovations in Life Sciences, including: 

• How to Foster Meaningful and Compliant Relationships with Patients and 

Physicians 

• Maximize Resource Allocation, Avoid Bottlenecks, and Bring Increased 

Effi ciency to Your Clinical and Regulatory processes 

• Determine the Impact of Electronic Medical Records on Your Impact Today 

and Innovate for the Future 

• Leverage the Impact of Mobile Devices to Improve Internal 

Communications and External Collaboration 

• Gain New Effi ciencies and Time Savings through Effective Clinical Trial 

Management Technologies 

• Increase Operational Effectiveness through the Development of Advanced 

Translational Medicine Models 

• Enable Global Collaboration and Compliance with Regulatory Bodies 

• Hear the Latest Trends and Innovations around Global Submissions 

• Utilize Virtual and Collaborative Technologies to Improve Speed and 

Decision Making Ability 

• And Much More! 

Premier Sponsor: 

Bio-IT World 

Subscribers receive 

10% off standard 

registration fees! 

Use code C210BIO 

when registering! 

Offi cial Media Partner: 

To Register Now, Call 866-207-6528 or Visit Our Website www.LSInnovation.com

Up Front - CHI Conferences - Cambridge Healthtech Institute

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?