Stacie is a pharmaceutical R&D and biotech leader with expertise in AI and machine learning applications for drug discovery. At BioSymetrics she guides the company on its drug discovery and partnering strategies, with a focus on translating human-relevant disease biology. Prior to BioSymetrics, Stacie led collaborations and partnerships in the AI-powered drug discovery space as Vice President and Head of AI Molecular Screening Partnerships at Atomwise. Previously she established and co-led the Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium, a public-private partnership developing machine learning tools to accelerate drug discovery. She worked at GSK for more than 13 years, starting as a process chemist and moving up into R&D strategy and operations roles where she led several change initiatives and teams. Stacie holds a B.S. in Chemistry from University of California Berkeley and a Ph.D. in chemistry from University of California Irvine.
The future of drug development is likely to be deeply impacted by machine learning in a multitude of ways. This panel will reflect on the past, present, and future of what has made drug discovery flourish and fail; with a special focus on the technology driving cutting-edge precision medicine.