Dr. Subha Madhavan, Ph.D. - Vice President & Head of AI/ML, Quantitative & Digital Sciences, Global Biometrics & Data Management, Pfizer - Leveraging Data And Artificial Intelligence To Get Transformative Medicines to Patients Faster

Send us Fan MailDr. Subha Madhavan, Ph.D. is Vice President & Head of AI/ML, Quantitative & Digital Sciences, Global Biometrics & Data Management, at Pfizer ( https://www.pfizer.com/ ), where she works at the interface of science, technology, and business, helping to shape various aspects of their biopharma focus from small molecule design, to precision medicine, to global access in the future. Dr. Madhavan’s responsibilities over her career have included initiating, designing, and executing several large national and international clinical research programs, including Cancer Moonshot, The Cancer Genome Atlas, Clinical Proteomic Tumor Analysis Consortium, and Human Cell Atlas, and she has put together an impressive portfolio of experience in oncology R&D, precision medicine, digital health, data science & analytics, bioinformatics, product development, clinical informatics, and health IT. Before joining Pfizer, Dr. Madhavan was AstraZeneca's Head of Data Science, Oncology R&D where she led cross-functional teams in early oncology, clinical development, R&D strategy, precision medicine, and competitive intelligence in bringing life-changing therapies to patients. Previously Dr. Madhavan was the Director of the Innovation Center for Biomedical Informatics (ICBI) at the Georgetown University Medical Center, Associate Professor in the Department of Oncology, and chief Data Scientist for the Georgetown University Medical Center with responsibility for all data-related research initiatives. Dr. Madhavan has a Master’s degree in Computer Information Systems from University of Maryland and a Ph.D. in Molecular Biology and Biological Sciences from the Uniformed Services University for the Health Sciences through a highly ranked Indo-US Collaborative program. She received post-doctoral training in computational biology at Johns Hopkins University School of Medicine. Support the show