Session Chair Profile
Ph.D., Associate Director, Precision Medicine Initiatives, GNS Healthcare, Inc.
Dr. Diane Wuest develops strategic relationships with precision medicine partners to develop and commercialize computer models capable of elucidating disease mechanisms, advancing drug discovery and development, and improving patient care. Diane manages ongoing alliances and leverages internal analytic and product development teams to implement company-wide initiatives. Prior to GNS Healthcare, Diane worked at Genentech and obtained a Ph.D. in chemical and biomolecular engineering from the University of Delaware. Diane holds a B.S. in chemical engineering from Cornell University.
Session Abstract – PMWC 2018 Silicon Valley
Session Synopsis: In order to facilitate the identification of targets or to provide individualized patient care, the ultimate practice of precision medicine, optimal use of the wide variety of translational data collected on patients is of critical importance. Yet, it is difficult to identify biomarkers with traditional methods given the much larger number of variables measured, compared to the number of patients enrolled in a clinical trial. As a result, very few organizations are leveraging all their data assets to identify what treatments work best for individual patients in an unbiased manner. As the data collected in clinical trials and during a patients’ life journey increases exponentially, this session aims to showcase how machine learning is a critical component to making personalized medicine a reality at the example of predictive biomarker identification, the development of holistic solutions for patients with complex diseases and its potential to impact value based pricing strategies.