Chai Discovery Secures $70M Series A for AI Molecular Design

Theaiinsider

San Francisco, CA – Chai Discovery, an artificial intelligence company at the forefront of molecular design, has successfully closed a $70 million Series A financing round, bringing its total funding to $100 million. This significant investment, led by Menlo Ventures through its Anthology Fund—a joint initiative with AI research powerhouse Anthropic—underscores the growing confidence in AI’s transformative potential for drug discovery and therapeutic development.

The funding round saw participation from a diverse group of new investors, including Yosemite, DST Global Partners, SV Angel, Avenir, and DCVC, alongside continued backing from existing investors like Thrive Capital, OpenAI, Dimension, Neo, Lachy Groom, and Fred Ehrsam. This collective support signals a strong belief in Chai Discovery’s mission to revolutionize how new medicines are brought to market.

Founded in 2024 by Joshua Meier (formerly of AI drug discovery firm Absci, Facebook AI, and OpenAI), Jack Dent (an engineering and product leader from Stripe), and AI researchers Matthew McPartlon and Jacques Boitreaud, Chai Discovery aims to shift biology from a trial-and-error science to a precise engineering discipline. The company develops and deploys frontier AI models designed to predict and reprogram the intricate interactions between biochemical molecules, which are the fundamental building blocks of life. This approach seeks to drastically accelerate the creation of life-changing therapeutics, a process historically plagued by high costs, lengthy timelines, and a staggering 90% failure rate for drug candidates.

A cornerstone of Chai Discovery’s innovative platform is its recently unveiled Chai-2 model. This breakthrough AI model for “fully de novo antibody design” boasts an impressive success rate, achieving a “near-20% hit rate” in generating novel antibody binders from scratch. This represents a monumental leap compared to traditional laboratory methods, which often necessitate screening millions to billions of antibodies to find viable hits, or previous computational approaches that yielded only a 0.1% success rate. Chai-2’s capability to design targeted antibodies with such precision and speed—reportedly solving complex problems in weeks that previously took years and millions of dollars—positions it as a “Photoshop for proteins,” enabling rapid and precise atomic-level molecular engineering.

The strategic involvement of Menlo Ventures’ Anthology Fund, a $100 million initiative specifically dedicated to backing AI pioneers leveraging Anthropic’s technology, highlights the deep integration of cutting-edge AI research into the biotech sector. Companies supported by this fund gain not only financial backing but also access to Anthropic’s advanced AI models and research, along with Menlo’s extensive company-building expertise. This partnership aims to accelerate the development of groundbreaking AI applications, particularly in fields like healthcare and scientific research.

Further bolstering Chai Discovery’s credibility and strategic direction is the addition of Mikael Dolsten, M.D., PhD., former Chief Scientific Officer at Pfizer, to its board of directors. Dolsten’s extensive experience, which includes advancing 150 molecules into clinical trials and delivering 36 approved medicines during his tenure at Pfizer, will be invaluable as Chai Discovery transitions its computational designs into real-world therapeutic applications.

With this fresh capital, Chai Discovery plans to further enhance its AI platform, pursue the design of previously inaccessible molecules, and strategically onboard select partners within the biotech sector. This funding is poised to significantly contribute to the broader trend of AI revolutionizing drug discovery, moving beyond traditional screening to enable the design of entirely new molecules and even predict manufacturability early in the development process, ultimately promising faster, more effective, and more accessible medicines for the future.