October 13-14 | UC Berkeley

 

2026 Annual Symposium on Risks and Opportunities of AI in Pharmaceutical Medicine

 

Accelerating Drug Development Through Agentic AI

sponsors
 

SAVE THE DATE    ·    OCTOBER 13-14, 2026    ·    BERKELEY, CALIFORNIA

About the Symposium

The 2026 Annual Symposium on Risks and Opportunities of AI in Pharmaceutical Medicine is jointly sponsored by the American Statistical Association, Amgen, Genentech, Northeastern University, Novo Nordisk, Pfizer, and the University of California at Berkeley. The symposium will take place October 13–14 at the University of California at Berkeley.

Early bird registration opens in April of 2026.


Where Will the AI Revolution Take Pharmaceutical Science?

Our world increasingly relies on data and computing to create knowledge, to make critical decisions, and to better predict the future. Data science has emerged to support these data-driven activities by integrating and developing ideas, concepts, and tools from computer science, engineering, information science, statistics, and domain fields. Data science now drives fields as diverse as biology, astronomy, material science, political science, and medicine—not to mention vast tracts of the global economy, key government activities, and quotidian social and societal functions.

The pharmaceutical enterprise has been slower to respond, especially to the rapid developments in AI, but tectonic shifts are underway in approaches to the discovery, development, evaluation, registration, monitoring, and marketing of medicines for the benefit of patients and the health of the community.

While there is much discussion about the potential of AI and modern machine learning tools to transform the drug development paradigm, there is a growing recognition of the paucity of research about the opportunities, inevitable pitfalls, and unintended consequences of the digital revolution in this important area of application. As we move toward personalized and truly evidence-based medicine, the use of AI and machine learning to optimize drug deployment raises a whole different set of challenges.

This forum is, therefore, expected to serve as a platform for distinguished statisticians, data scientists, regulators, and other professionals to address the challenges and opportunities of AI in pharmaceutical medicine; to foster collaboration among industry, academia, regulatory agencies, and professional associations; and to propose recommendations with policy implications for proper implementation of AI in promoting public health.

Key Details

Program Co-Chairs
Demissie Alemayehu, Pfizer
David Madigan, Northeastern University

Contact Us
For program-related queries, please reach out to Demissie Alemayehu; Demissie.Alemayehu@pfizer.com.