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OpenAI researcher Miles Wang in talks to launch $2 billion AI drug discovery startup

Miles WangAn OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery is leaving the maker of ChatGPT to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.

Wang is in talks to raise about $200 million at a valuation of $2 billion, two of the people said. Lightspeed is in talks to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.

Wang disputed the story’s funding figures and description of the company, but did not specify the correct figures or details. Lightspeed did not respond to a request for comment.

Funding discussions point to investor interest in applying AI to advance life sciences. Chai Discovery, a two-year-old startup that develops artificial intelligence models that can predict molecular interactions to identify new drugs, announced Tuesday that it raised $400 million with a valuation of 3.8 billion dollars. (Co-founder Josh Meier also spent time at OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a 2.1 billion dollars Series B in May.

Wang’s new startup may be working on artificial intelligence models that will help find new uses for existing drugs and possibly those that previously failed trials, a pair of sources told TechCrunch. Finding new uses for FDA-approved drugs can generate revenue significantly faster than developing new drugs from scratch, since the safety of these drugs has already been proven.

Wang joined OpenAI in 2024 after leaving Harvard, where he was working on a computer science degree. (In recent years, investors are once again comfortable betting on young founders who I haven’t finished college.)

At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.

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