Chai Discovery and BMS Advance AI Antibody Discovery

San Francisco, California, August 20, 2026

AI Models Support Next-Generation Antibody Discovery

Under the collaboration, Bristol Myers Squibb will use Chai Discovery’s advanced AI models and platform capabilities, including molecular folding and molecular design technologies, to support antibody discovery programs across its portfolio. Chai’s technology is designed to predict and model molecular interactions and generate new biomolecular designs based on defined characteristics. By applying computational modeling to biological structures and molecular interactions, the platform aims to help researchers evaluate potential therapeutic candidates more efficiently during the discovery process. The collaboration is expected to support BMS’s broader objective of developing an AI-powered, continuously learning drug discovery system, potentially allowing computational methods and experimental research to work together throughout the early stages of therapeutic development. Chai Discovery said its AI models are designed to reason about biological structure and function and generate molecular designs from scratch. The company is particularly focused on applying these capabilities to therapeutic targets that have historically presented challenges for conventional drug discovery approaches. By using AI to explore molecular possibilities, researchers may be able to investigate a broader range of candidate designs before progressing promising molecules into laboratory testing. The collaboration therefore represents an effort to integrate advanced computational science into the established antibody discovery workflow of a major biopharmaceutical company.

Combining AI Innovation With Pharmaceutical Expertise

The partnership brings together Chai Discovery’s computational technology with Bristol Myers Squibb’s experience in therapeutic research and development. For pharmaceutical companies, antibody discovery can involve extensive experimentation to identify molecules with appropriate binding, specificity and other desired characteristics. AI-based molecular design approaches seek to reduce some of the time and resources required to explore these possibilities by helping scientists prioritize candidates for further investigation. Chai Discovery described Bristol Myers Squibb as its latest biopharmaceutical collaborator as the company expands the application of its technology across drug discovery. According to Chai, its platform is intended to help scientists design biomolecules with specific properties and compress discovery cycles, potentially enabling researchers to pursue therapeutic targets that have been difficult to address using traditional methods. The technology remains a discovery and design tool, and the collaboration does not indicate that any specific AI-generated antibody has been approved or demonstrated clinical efficacy. Candidates identified through discovery programs would still need to undergo appropriate preclinical development, clinical evaluation and regulatory review before they could become medicines.

Expanding the Role of AI in Drug Development

The collaboration reflects the broader evolution of AI-enabled pharmaceutical research, where machine learning and computational modeling are increasingly being incorporated into molecular design and biological research. Chai Discovery, founded in 2024 by Joshua Meier, Jack Dent, Matthew McPartlon and Jacques Boitreaud, is developing AI systems intended to bring greater computational precision and scalability to therapeutic discovery. The San Francisco-based company brings together expertise from AI research, molecular design and technology development. For Bristol Myers Squibb, the collaboration provides access to AI capabilities that can complement its existing scientific infrastructure and therapeutic expertise. For Chai Discovery, working with a major biopharmaceutical company provides an opportunity to apply its technology to real-world antibody discovery programs and diverse drug targets. The companies’ collaboration could therefore contribute to the continuing development of computationally assisted drug discovery, particularly as pharmaceutical researchers seek faster and more systematic approaches for identifying promising therapeutic candidates. While the ultimate value of the collaboration will depend on research outcomes, the agreement underscores the growing importance of AI-powered molecular design in modern biopharmaceutical innovation.

Source: Chai Discovery, Bristol Myers Squibb press relese