04.06.2016 Views

UCSF HELEN DILLER FAMILY COMPREHENSIVE CANCER CENTER

kmUU300MXic

kmUU300MXic

SHOW MORE
SHOW LESS

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

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Presentations<br />

Determining barriers to effective data sharing in cancer genomic<br />

sequencing initiatives: A Global Alliance for Genomics and Health<br />

(GA4GH) survey.<br />

Authors*: Jeremy Howard Lewin, Daniel J Vis, Emile E. Voest, Rachel Liao, Petra M Nederlof, Barbara A. Conley,<br />

David B. Solit, Christopher L. Corless, Paulo V Campregher, Vanessa Tyrell, George Chong, Michael Watson,<br />

Sun Young Rha, Tim Maughan, Mark Caulfield, Vladimir Lazar, Laura Esserman, Charles L. Sawyers,<br />

Lillian L. Siu, Mark Lawler<br />

Abstract #: 11502<br />

Presentation Date/Time: Tuesday, June 7: 8:00 - 11:00 AM<br />

Location: S100a<br />

Session: Tumor Biology<br />

Citation: J Clin Oncol 34, 2016 (suppl; abstr 11502)<br />

Esserman Research Interests: Dr. Esserman, surgeon & breast cancer oncology specialist, is the Carol Franc<br />

Buck Breast Care Center Director and co-leads the Breast Oncology Program. Her research is on improving<br />

healthcare value through integrating translational science, clinical informatics, systems re-engineering<br />

& clinical care delivery. In 2005, she received the NCI SPORE Investigator of the Year Award. In 2016 she<br />

received the Arbuckle Award from Stanford Graduate School of Business for Excellence in Management &<br />

was named to TIME’s 100 most influential people list. She is PI of the I-SPY TRIAL program, now a model for<br />

translational research & innovation in clinical trial design. She launched the Athena Breast Health Network to<br />

follow women from screening through treatment & outcomes, incorporating the latest in molecular testing &<br />

web-based tools. Athena just launched the WISDOM study to compare personalized vs annual breast cancer<br />

screening in 100,000 women and to predict who gets what kind of cancer.<br />

http://profiles.ucsf.edu/laura.esserman<br />

*<strong>UCSF</strong> authors in bold<br />

89

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!