LabAutomation 2006 - SLAS

LabAutomation2006
12:00 pm Tuesday, January 24, 2006 Track 4: Informatics Room: Madera
Wyndham Palm Springs Hotel
Igor Fomenko
Co-Author(s)
Amgen
Peter Miu
Newbury Park, California
Mark Durst
ifomenko@amgen.com
David Balaban
Novel Data Analysis for In Vitro Electrophysiological Assays in HTS
Cardiac potassium ion channel, known as hERG, plays an important role in determining safety margins for therapeutic dosing. An
electrophysiology based cell assay has been developed and validated to establish the concentration-response (CR) relationship of known
hERG channel blockers. This assay platform is considered as the Gold Standard for studying ion channels. However due to the assay
parameters and protocols, this hERG assay presents a challenge in data analysis. For instance, 4 to 6 concentrations per CR curve are
typically generated to determine drug potency. Hence, reliable estimate of a single CR curve is often problematic. On the other hand the
repeated measurements from the same population of cells are possible (3 –11 cells). The proposed analytical technique takes into the
account the biological variability of the responses across the cells and quantifies both the consistency of the assays for the population
of the cells of the same type as well as this variability. The estimates of the assay’s characteristics are based on nonlinear mixed effects
theory of statistics. We present this approach on the example of the safe blocker Quinidine using statistical packages S-Plus and R. Such
approach allows effective and automated analysis of HTS data with repeated measurements.
3:00 pm Tuesday, January 24, 2006 Track 4: Informatics Room: Madera
Wyndham Palm Springs Hotel
Gary Kramer
National Institute of Standards and Technology
Gaithersburg, Maryland
gary.kramer@nist.gov
Interchanging Analytical Data and Metadata Using the Analytical Information Markup
Language (AnIML)
Interchanging analytical data and their associated “scientific metadata” across space and time, from application to application, and to/from
applications and databases has often been hampered by multiple, incompatible data formats. The rapid pace of information technology
and computing hardware innovation has exacerbated this problem. Analytical information stored on early digital media (let’s say 8-inch
floppy disks) 20 years ago may be less accessible today than such information stored in a paper format 20 years prior.
ASTM SubCommittee E13.15 on Analytical Data is creating AnIML to describe chromatography and spectroscopy data and metadata.
Based on XML (eXtensible Markup Language) and its associated technologies, AnIML facilitates access to analytical data by building in
descriptions of the data and metadata with delimited tags in the same way that HTML (HyperText Markup Language) describes the display
of items on a webpage. AnIML is built around a core schema that defines ways for describing almost any data. Technique Definition files
are created to constrain the data description mechanisms for a given analytical technique to those commonly accepted, to delineate the
metadata items commonly associated with such domain data, and to permit content extension by vendors and users without changing the
core schema. Once in AnIML format, analytical data can be interchanged over the web, converted to other formats, validated, or visualized
in multiple formats using existing XML-based tools. AnIML ensures the integrity of the data through the use of digital signatures and
provides for the data tracking, verification, and validation necessary for use in regulated industries.
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