“We are
aiming to have AI-designed drugs entering clinical trials by the end of 2025,”
said Demis Hassabis, CEO of Isomorphic Labs and a Nobel Prize laureate, during
a panel discussion at the World Economic Forum in Davos. “That’s our goal.”
The potential
of AI in drug discovery is vast. Instead of spending years manually testing
compounds, AI can analyze large datasets to detect patterns and predict which
molecules might evolve into breakthrough drugs. This could dramatically accelerate
the development process, reduce costs, and potentially unlock new cures.
Currently,
there are more than 460 AI startups working on drug discovery, with over a
quarter of them based in Europe. To date, the sector has seen investments
surpassing $60 billion, with funding continuing to grow.
However, drug
discovery is only part of the equation. The real impact will come when major
pharmaceutical companies decide to scale up production and bring these drugs to
market. This is why partnerships between AI-driven companies and big pharma are
particularly exciting.
In 2024,
Isomorphic Labs secured a $45 million deal with Eli Lilly to advance AI-based
research into small molecule therapeutics. This agreement could also see
Isomorphic earn up to $1.7 billion in performance-based milestones.
Additionally, the company has partnered with Swiss biotech firm Novartis.
“We’re
already working on real drug programs,” Hassabis told Bloomberg Television
following these announcements. “We expect to see the first AI-designed drugs in
clinical trials within the next few years.”
Exscientia, a
company that emerged from Dundee University in 2012, was one of the first to
apply AI to drug discovery. In 2024, Exscientia advanced its first AI-designed
drug candidate into human trials within a year—a process that typically takes
five years. The US-based company Recursion acquired Exscientia for $688 million
in November.
These are
just two of the most prominent examples in a booming AI drug discovery market,
which is also experiencing consolidation. Smaller companies are also exploring
specialized applications, such as CardiaTec, based in Cambridge, UK, which uses
AI to develop treatments for heart conditions, and Multiomic Health in London,
which is focused on metabolic diseases.
While AI
promises to accelerate the drug discovery process, it’s not a one-size-fits-all
solution. While AI can speed up the identification of viable drug candidates,
the time-consuming stages—such as physical lab tests, clinical trials, and
regulatory approvals—will still require traditional approaches. However, AI's
true strength lies in its ability to pinpoint promising drug candidates early,
saving researchers valuable time and potentially unveiling new therapeutic
possibilities.
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