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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<\/a>, offer an expensive scattershot approach \u2014 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.<\/p>\n 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\u2019s most influential investors, making it one of the flashiest firms in a growing industry. In December, the company completed its Series B<\/a>, bringing in an additional $130 million and a valuation of $1.3 billion.<\/p>\n Last Friday, Chai also announced a partnership with Eli Lilly, a deal<\/a> in which the pharmaceutical giant will use the startup\u2019s software to help develop new medicines. Chai\u2019s algorithm, called Chai-2, is designed to develop antibodies \u2014 the proteins necessary to fight illnesses. The startup has said it hopes to serve as a kind of\u00a0\u201ccomputer-aided design suite\u201d for molecules.<\/p>\n It\u2019s a critical moment for Chai\u2019s particular field. The startup\u2019s deal was announced shortly before Eli Lilly said it would also collaborate with Nvidia on a $1 billion partnership<\/a> to create an AI drug discovery lab in San Francisco. This \u201cco-innovation lab,\u201d as it\u2019s being called, will combine big data, compute resources, and scientific expertise, all in an attempt to accelerate the speed of new medicine development.<\/p>\n The industry isn\u2019t without its detractors<\/a>. Some industry veterans seem to feel that \u2014 given how difficult traditional drug development is \u2014 these new technologies are unlikely to have a major impact<\/a>. However, for every naysayer, there seem to be just as many believers.<\/p>\n Elena Viboch, managing director at General Catalyst \u2014 one of Chai\u2019s major backers<\/a> \u2014 told TechCrunch that her firm is confident that companies that adopt the startup\u2019s services will see results. \u201cWe 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,\u201d Viboch said. \u201cIn practice that means partnering in 2026 and by the end of 2027 seeing first-in-class medicines enter into clinical trials.\u201d<\/p>\n Aliza Apple, the head of Lilly\u2019s TuneLab program \u2014 which uses AI and machine learning to advance drug discovery \u2014 also expressed confidence in Chai\u2019s product. \u201cBy combining Chai\u2019s generative design models with Lilly\u2019s 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,\u201d she said.<\/p>\n Techcrunch event<\/p>\n \n\t\t\t\t\t\t\t\t\tSan Francisco<\/span> Chai may have been founded less than two years ago, but the startup\u2019s 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\u2019s 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 \u2014 that is, a company focused on the study of proteins.<\/p>\n Altman \u201cmessaged me to say that everyone at OpenAI thought highly of him and asked if I thought he\u2019d be open to working with them on a proteomics spinout,\u201d Dent said. Dent told Altman \u201cof course,\u201d but there was just one hitch: Meier didn\u2019t feel like the technology was quite \u201cthere\u201d yet. The AI tech behind such firms \u2014 which leverage powerful algorithms \u2014 was still a growing field and far from where it needed to be.<\/p>\n
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