Generative AI in Medical Research & Drug Development: Hype or Reality?

Day 2 Plenary Session 1 (Chair, Margret Gamalo, Pfizer Inc.)

• “Empowering Insights in the All of Us Research Program: A Statistical Perspective on the Transformational Role of AI and ML”, Qingxia ‘Cindy’ Chen, Biomedical Informatics, and Ophthalmology & Visual Sciences at Vanderbilt University Medical Center (25 min)
• “The Generalist Medical AI Will See You Now”, Pranav Rajpurkar, Ph.D., Harvard University (25 min)
• Lessons from pre-trained observational large longitudinal models in OHDSI (APOLLO),  Marc Suchard, UCLA  (25 min).

Break/Posters

Day 2 Plenary Session 2 (Chair, Bingzhi Zhang, Sanofi)

• “Generative Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes”, Yuanjia Wang, Columbia University   (25 min)
• “Machine Learning for Causal Inference”, Stefan Wager, Stanford University (25 min)
• “Leveraging the Power of Large Language Models (LLMs) by Statisticians for Pharmaceutical Research & Development”, Junshui Ma, Head of the Biometrics Research Department, Merck Research Lab.  (25 min)

Lunch

Day 2 Plenary Session 3 (Chair, Emre Kiciman, Microsoft)

• “The Role of Targeted Machine Learning in a Causal Roadmap for Generating High-Quality Real-World Evidence, Lauren Elizabeth Eyler Dang, National Institute of Allergy and Infectious Diseases Biostatistics Research Branch (25 min)
• “The multitude of group affiliations: Algorithmic Fairness, Loss Minimization and Outcome Indistinguishability”, Omer Reingold, Stanford University (25 min)
• Modeling Covid-19 Immunological Reactions and Clinical Susceptibility in the Context of Long-Term Follow-up of a Prospective Cohort of Healthcare Workers, Noam Barda, Ben-Gurion University. (25 min)
• “Drugs in Clinical Trials Out of Generative AI”, Petrina Kamya, Insilico Medicine (25 min)

Break