DeepMind’s Hassabis Sees AI-Designed Drug Trials This Year
(Bloomberg) — Google DeepMind spinoff Isomorphic Labs expects research of drugs it designed using artificial intelligence will begin this year, according to its Nobel Prize-winning chief executive officer.
“We’ll hopefully have some AI-designed drugs in clinical trials by the end of the year,” Demis Hassabis, who leads both Alphabet Inc. subsidiaries, said on a panel at the World Economic Forum in Davos. “That’s the plan.”
Isomorphic Labs is working on shortening the drug discovery process from a decade or more to “weeks or months,” Hassabis said. He and another DeepMind scientist, John Jumper, shared the 2024 Nobel Prize in Chemistry with a US professor for their breakthrough research in predicting protein structures.
AI’s ability to process huge amounts of data can potentially help speed drug development, but most major pharmaceutical companies have taken a measured approach to using the emerging technology, according to a December report led by Bloomberg Intelligence analyst Andrew Galler. Initial data for clinical candidates has been mixed, the report found.
Even so, tech companies and pharmaceutical giants are increasingly partnering together. Last year, Isomorphic Labs announced strategic research collaboration agreements with Eli Lilly & Co. and Novartis AG.
Alphabet created the subsidiary in 2021 to commercialize DeepMind’s AI for drug discovery. DeepMind first released AlphaFold, its tool for predicting protein patterns, in 2018. Now in its third iteration, AlphaFold can model a range of molecular structures, including DNA and RNA, and predict how they interact with one another.
Hassabis also cautioned that AI companies were likely years away from so-called artificial general intelligence, a benchmark in which the algorithms would surpass humans on most tasks.
“A small handful of probably big breakthroughs are needed,” he said. “It might be none, it might be just scaling from here. But I suspect that there may be one or two things that are missing, which will take more of a five-year timescale.”
(Updates with additional comments on AGI in final paragraph)
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