Mr Viral
Google DeepMind spinoff Isomorphic Labs expects testing on its first AI-designed drugs to begin this year, as tech startups race to turn algorithmic magic into actual treatments.
“We’ll hopefully have some AI-designed drugs in clinical trials by the end of the year,” the firm’s Nobel Prize-winning CEO Demis Hassabis told a panel at the World Economic Forum in Davos this week. “That’s the plan.”
The potential of AI-powered drug discovery is huge. Instead of spending years or even decades testing chemicals by hand, machine learning algorithms can sift through mountains of data to spot patterns and predict which molecules could make the next miracle drug. This could lead to faster drug development, cheaper costs, and new cures.
By one estimate, there are over 460 AI startups currently working on drug discovery, of which over a quarter come from Europe. Globally, more than $60bn has been invested into the space so far, and the funding flood isn’t showing any signs of letting up.
Yet discovering the drugs is merely one step in the process. it’s only when big pharma decides they’re worth manufacturing, marketing, and distributing that it’ll make a real difference to the likes of you and me.
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That’s what makes some of the recent hookups between pharma behemoths and AI startups particularly exciting.
Last year, Isomorphic Labs inked a $45mn deal with Eli Lilly to collaborate on AI-based research into small molecule therapeutics. Under the agreement, Isomorphic is also eligible to receive up to $1.7bn in “performance-based milestones.” The company also signed a similar collaboration with Swiss biotech Novartis.
“We’re already working on real drug programs,” Hassabis told Bloomberg Television in an interview shortly following the announcements. “I would expect in the next couple of years the first AI-designed drugs in the clinic.”
Exscientia, which spun out from Dundee University in 2012, was among the first to apply AI to drug discovery. In 2024, the company advanced its first AI-designed drug candidate into human clinical trials, achieving this milestone in just 12 months — a process that typically takes around five years. US rival Recursion acquired the Oxford-based company for $688mn in November.
These are two big examples of an AI-driven drug discovery market that’s booming, and increasingly, consolidating. However, there are also plenty of early-stage companies working on more niche applications of the technology. These include Cambridge, UK-based CardiaTec, which is using AI to find new drugs to treat heart conditions, and London-headquartered Multiomic Health, which is working on formulas to treat metabolic diseases.
Despite all the potential though, AI isn’t a silver bullet for drug discovery. While it can drastically speed up finding the right compounds needed to make new drugs, the most time-consuming steps — like wet lab tests with physical samples, clinical trials, and FDA approvals — aren’t going anywhere. Still, AI’s real power lies in that critical first phase: zeroing in on targets that might’ve otherwise slipped through the cracks, saving researchers time and possibly even unlocking new treatments.
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