Chai Discovery partners with Bristol Myers Squibb for AI antibody discovery
By Dr. Zubair Khalid, DVM, MS, PhD ·
Key Takeaways
- Chai Discovery, an AI-native drug discovery firm, has partnered with Bristol Myers Squibb to leverage artificial intelligence for antibody discovery, aiming to accelerate the identification and engineering of novel protein therapeutics.
- The collaboration integrates Chai's machine-learning platform, designed to predict and engineer protein structures, with Bristol Myers Squibb's established drug development expertise.
- This strategic alliance reflects a broader industry trend where major pharmaceutical companies are increasingly engaging with AI startups to expedite the discovery of biologic drugs, a process traditionally characterized by lengthy screening periods.
- Chai's AI technology, built upon deep learning advancements, is intended to design antibodies with enhanced specificity and improved developability, potentially reducing the time and cost associated with early-stage research.
- The application of AI in this context could significantly shorten the multi-year timelines typically associated with traditional antibody development, thereby facilitating the faster introduction of new antibody-based therapies to market.
Chai Discovery has entered a collaboration with Bristol Myers Squibb to apply artificial intelligence to antibody discovery. The deal comes about one month after Chai closed a $400 million Series C funding round, according to a report from Fierce Biotech.
The partnership brings together Chai’s AI-driven protein-design platform with Bristol Myers Squibb’s drug-development capabilities. The specific financial terms and targets of the collaboration were not detailed in the announcement. Chai Discovery is an AI drug-discovery firm focused on using machine-learning models to predict and engineer novel proteins, including antibodies.
Relevance to the life sciences
The collaboration reflects a growing trend in biotech: large pharmaceutical companies are increasingly turning to AI-native startups to speed up the discovery of biologic drugs. Traditional antibody development is slow and labor-intensive, often requiring years of screening. AI platforms can simulate and optimize protein structures in silico, potentially cutting months or years from early-stage research. Chai’s technology, which builds on advances in deep learning, aims to design antibodies with greater specificity and developability. If successful, this approach could lower the cost of bringing new antibody-based therapies to market and expand the range of druggable targets.
Source: original report