Building a Responsible AI Framework for Pharma at Eli Lilly

In this session, Brian shares Lilly's perspective on what makes AI in pharma fundamentally different from other industries — the unique intersection of scientific rigor, engineering velocity, and regulatory accountability — and what those constraints have taught his team about building AI systems that are fast, reproducible, and trustworthy. From GPU-scale compute to experiment tracking and evaluation, he'll discuss how Lilly is operationalizing AI across thousands of scientists and what that journey looks like when the cost of being wrong isn't a rollback — it's a decade of lost research.