Chai Discovery and Bristol Myers Squibb Partner to Advance AI-Driven Antibody Discovery

Chai Discovery is collaborating with Bristol Myers Squibb to use artificial intelligence for therapeutic antibody discovery, bringing AI-based molecular folding and design capabilities into the biopharmaceutical company’s discovery programs.

AI Models to Support Antibody Candidate Discovery

Under the collaboration, Bristol Myers Squibb will leverage Chai Discovery’s AI models and platform capabilities to support the identification and design of antibody candidates across its portfolio. The partnership also supports the company’s broader effort to build an AI-powered discovery system that can continuously learn from experimental data and improve future design cycles.

Chai Discovery develops computational tools that predict and reprogram molecular interactions. Its models can generate biomolecules according to defined structural or functional criteria, allowing researchers to evaluate potential candidates earlier in the discovery process.

For antibody discovery, these capabilities can help scientists explore molecular designs and interactions that may be difficult to identify through conventional experimental approaches alone. The platform’s molecular folding and design models provide computational predictions that can inform candidate selection before laboratory validation.

Computational Design Could Compress Early Discovery Cycles

Traditional antibody discovery often requires iterative cycles of target assessment, molecular generation, screening, optimization, and experimental validation. AI-based molecular design can shift part of this process into a computational environment, enabling researchers to evaluate a broader design space before committing resources to laboratory testing.

Chai’s technology uses predicted molecular structures and interactions to generate candidate biomolecules based on specified properties. The approach could expand access to previously difficult targets by allowing researchers to search larger molecular design spaces and prioritize candidates with desired characteristics.

The collaboration does not disclose specific targets, antibody programs, development candidates, financial terms, or timelines for clinical advancement.

Combining AI Development with Therapeutic Expertise

Joshua Meier, co-founder and chief executive officer of Chai Discovery, said the company will deploy its technology across diverse drug targets through the collaboration. He highlighted the combination of Chai’s AI models with Bristol Myers Squibb’s therapeutic development expertise as a potential way to accelerate the progression from molecular concepts to viable therapeutic candidates.

The partnership adds Bristol Myers Squibb to Chai Discovery’s growing group of biopharmaceutical collaborators. For Chai, the relationship provides an opportunity to apply its molecular design technology across a large-scale therapeutic discovery portfolio.

Path Forward

The immediate focus will remain on discovery-stage antibody programs rather than clinical development. As the collaboration progresses, its value will depend on whether AI-generated designs translate into experimentally validated antibodies with the properties required for therapeutic development.

The partnership also reflects a broader shift in drug discovery toward integrated computational and experimental workflows. For large biopharmaceutical companies, combining proprietary biological data and therapeutic expertise with external AI models could provide new routes for candidate generation and target exploration.

Specific antibody candidates, development milestones, and clinical timelines have not been disclosed.

Reference

Chai Discovery Announces Collaboration with Bristol Myers Squibb to Advance AI-Driven Antibody Discovery