Illustration by TIME; reference image courtesy of Andrew Hopkins

In 2022, medical researchers took tumor samples from 143 patients with advanced blood cancers, and tested them against 139 cancer drugs. An AI system judged which drugs had been most effective against each patient’s tumor sample, and patients were matched with the therapy predicted to be most effective.

Of the 56 patients given personalized drug recommendations, 54% had their cancer kept under control nearly a third longer compared with their prior therapy. Matching cancer patients to the right drug is a difficult task—in recent decades physicians have analyzed the genomes of cancers to prescribe a handful of purpose-built drugs; however, the new approach allows a broader range of drugs to be used in a more targeted way. This, says Andrew Hopkins, founder and CEO of U.K.-based biotech company Exscientia, which developed the drug-selection technology, is one example of how AI is already improving outcomes for patients.

While the AI used in this trial was relatively simple, Exscientia is also building more complicated systems to design new drugs. Exscientia became the first company to enter an AI-designed drug into clinical trials in 2020—it took 12 months to identify the drug candidate (one that aims to treat obsessive-compulsive disorder), a process that can take many years with traditional methods. Since then, it has brought five more AI-designed drugs to clinical trials, including ones that target lung cancer and autoimmune diseases, says Hopkins.

Hopkins, 52, founded Exscientia in 2012, spinning the company out of his work at the University of Dundee, where he held the chairs of medicinal informatics and translational biology. Before that, he spent a decade at pharmaceutical giant Pfizer. Exscientia’s mission, he says, is to automate drug discovery in its entirety—identifying protein targets for drugs, designing drugs that are a good match for those targets, and, as in the 2022 study, selecting which drug from a range is best for a given patient.

In 1996, Hopkins was a Ph.D. student working in the lab to find drugs to treat HIV. One confounding issue with the virus was its adaptability, meaning it would often develop resistance to new drugs within weeks of their use. At 2 a.m. one night, Hopkins had an epiphany of sorts: if drug discovery could be automated using AI, the rate at which scientists found new treatments could accelerate rapidly. Hopkins was especially fond of late-night walks. “We used to have lab meetings at midnight,” Hopkins says. “We often used to go to the pub and then go back to the lab and carry on.”

Hopkins says he and his current team have the same spirit. “What’s incredible about the staff of Exscientia,” says Hopkins, “is how everyone is really sort of engaged in a mission: How do we improve and solve the problem of drug discovery?”

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