Drug discovery, the art of identifying new molecules to develop pharmaceuticals, is a notoriously time-consuming and difficult process. Traditional techniques, like high-throughput screening, offer an expensive scattershot approach — one that is not often successful. However, a new breed of biotech companies are leveraging AI and advanced data technologies in an attempt to accelerate and streamline the process.
Chai Discovery, an AI startup founded in 2024, is one such company. In a little over 12 months, its young co-founders have managed to raise hundreds of millions of dollars and rally the backing of some of Silicon Valley’s most influential investors, making it one of the flashiest firms in a growing industry. In December, the company completed its Series B, bringing in an additional $130 million and a valuation of $1.3 billion.
Last Friday, Chai also announced a partnership with Eli Lilly, a deal in which the pharmaceutical giant will use the startup’s software to help develop new medicines. Chai’s algorithm, called Chai-2, is designed to develop antibodies — the proteins necessary to fight illnesses. The startup has said it hopes to serve as a kind of “computer-aided design suite” for molecules.
It’s a critical moment for Chai’s particular field. The startup’s deal was announced shortly before Eli Lilly said it would also collaborate with Nvidia on a $1 billion partnership to create an AI drug discovery lab in San Francisco. This “co-innovation lab,” as it’s being called, will combine big data, compute resources, and scientific expertise, all in an attempt to accelerate the speed of new medicine development.
The industry isn’t without its detractors. Some industry veterans seem to feel that — given how difficult traditional drug development is — these new technologies are unlikely to have a major impact. However, for every naysayer, there seem to be just as many believers.
Elena Viboch, managing director at General Catalyst — one of Chai’s major backers — told TechCrunch that her firm is confident that companies that adopt the startup’s services will see results. “We believe the biopharma companies that move the most quickly to partner with companies like Chai will be the first to get molecules into the clinic, and will make medicines that matter,” Viboch said. “In practice that means partnering in 2026 and by the end of 2027 seeing first-in-class medicines enter into clinical trials.”
Aliza Apple, the head of Lilly’s TuneLab program — which uses AI and machine learning to advance drug discovery — also expressed confidence in Chai’s product. “By combining Chai’s generative design models with Lilly’s deep biologics expertise and proprietary data, we intend to push the frontier of how AI can design better molecules from the outset, with the ultimate goal to help accelerate the development of innovative medicines for patients,” she said.
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Chai may have been founded less than two years ago, but the startup’s origins began around six years ago, amid conversations between its co-founders and OpenAI CEO Sam Altman. One of those founders, Josh Meier, previously worked for OpenAI in 2018 on its research and engineering team. After he left the company, Altman messaged Meier’s old college friend, Jack Dent, to ask about a potential business opportunity. Meier and Dent had originally met in computer science classes at Harvard but, at the time, Dent was a Stripe engineer (another company Altman was an early backer of). Altman asked him if he thought Meier would be open to collaborating on a proteomics startup — that is, a company focused on the study of proteins.
Altman “messaged me to say that everyone at OpenAI thought highly of him and asked if I thought he’d be open to working with them on a proteomics spinout,” Dent said. Dent told Altman “of course,” but there was just one hitch: Meier didn’t feel like the technology was quite “there” yet. The AI tech behind such firms — which leverage powerful algorithms — was still a growing field and far from where it needed to be.
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