Session Abstract – PMWC 2022 Silicon Valley
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.
Session Chair Profile
Biography
Dr. Ansuman Satpathy M.D., Ph.D. in the Department of Pathology at Stanford University School of Medicine. He is a member of the Stanford Cancer Institute, the Parker Institute for Cancer Immunotherapy, the Immunology, Cancer Biology, and Biomedical Informatics Programs, Bio-X, and a faculty fellow in ChEM-H. Dr. Satpathy completed an M.D. and Ph.D. in immunology at Washington University in St. Louis, clinical residency in pathology at Stanford Hospital and Clinics, and postdoctoral training in genetics at Stanford University. Dr. Satpathy’s research group focuses on developing and applying genome-scale technologies to study fundamental properties of the immune system in health, infection, and cancer.
Session Chair Profile
Biography
Mark Jacobstein is the Executive Business Advisor and former CBO for Immunai, a high growth startup using single cell genomics and ML to reprogram the immune system. Mark came to Immunai from Guardant Health, where he spent four years as the CUEO. Prior Mark was CEO of mobile VOIP-pioneer iSkoot until its acquisition by Qualcomm. Mark was also an EVP at loopt (sold to GreenDot) and the co-founding President of Sequoia-backed Digital Chocolate, a pioneer in mobile games. In 1994 Mark founded Small World Sports, the world's first online fantasy sports business, and served as CEO until he sold the business to Paul Allen in 2002. Mark also co-founded Small World Software, which he sold to iXL, where he served as SVP of business development through their 1998 IPO.
Speaker Profile
Biography
Cornelis E.C.A. “Marcel” Hop is Vice-President at Genentech and supervising the DMPK department. He leads a team of about 85 scientists involved in acquisition and interpretation of ADME data in support of drug discovery and development ranging from early stage research to NDA and beyond. Before that, he was a Senior Director at Pfizer and a Senior Research Fellow at Merck and he received his Ph.D. from the University of Utrecht (The Netherlands). He has extensive experience in ADME sciences with a particular focus on PK optimization, human PK prediction, biotransformation, bioanalysis and the use of in silico approaches in drug discovery.
Speaker Profile
Biography
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.
Speaker Profile
Biography
A former neuroscience researcher, Andrea’s portfolio career has included leadership assignments at the intersection of science, technology and business development. She has built and led informatics and scientific teams across the entire pharmaceutical value chain. Most recently, Andrea focused on building the Pharma Artificial Intelligence market at NVIDIA. Through this experience she has travelled the world advising biopharmaceutical, academics, research institutes, and startups in the potential of machine learning and artificial intelligence across every discipline in our industry. Prior to her role at NVIDIA, Andrea held leadership positions at the Broad Institute of Harvard and MIT, Amgen, and Roche. In the last three years, Andrea’s work at Eli Lilly & Company has focused around empowering the LRL Research organization with greater computational, analytics-intense experimentation to raise the innovation of our scientists.