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

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

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

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

Funding discussions point to investor interest in applying AI to achieve breakthroughs in the life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced Tuesday that it has raised $400 million at a $3.8 billion valuation. (Co-founder Josh Mayer also came through OpenAI as a researcher.) Meanwhile, Google spinoff DeepMind Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.

Wang’s new startup may work on AI models that will help find new applications for existing drugs and possibly for those that have previously failed trials, several sources told TechCrunch. Finding new applications for FDA-approved drugs can lead to a significantly faster time to revenue than developing new drugs from scratch because these drugs have already been tested for safety.

Wang joined OpenAI in 2024 after leaving Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors have become comfortable again betting on young founders who haven’t graduated from college.)

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