Bristol Myers Squibb Partners with Chai Discovery to Use AI for Antibody Design

Bristol Myers Squibb's partnership with Chai Discovery represents a broader industry pivot toward AI-driven drug discovery. Traditionally, antibody development has been constrained by the wet-lab bottleneck: identifying viable candidates against complex or difficult-to-target antigens required months or years of iterative screening. Targets that are conformationally flexible, embedded in cell membranes multiple times, or historically "undruggable" posed particular challenges for conventional hybridoma and display library approaches.

Chai's platform reframes this challenge as a computational problem. By deploying generative models that predict molecular folding and biochemical function, the system can design antibody sequences and structures from scratch to meet defined biophysical constraints—compressing the early-stage pipeline from months into weeks. For BMS, this integration into a continuously learning discovery system potentially unlocks access to high-value targets that standard methods cannot address. Chai's existing partnerships with Eli Lilly, Pfizer, and Novartis suggest the company's approach has gained credibility across the sector; the BMS deal signals this model is becoming foundational rather than experimental.