Tapping into the drug discovery potential of AI
Plentiful financing and multiple pharma partnerships illustrate the burgeoning interest in applying artificial intelligence tools to drug research and development.
In April of this year, the German biotechnology company Evotec announced a phase 1 clinical trial on a new anticancer molecule. The candidate was created in partnership with Exscientia, a company based in Oxford, UK, that applies artificial intelligence (AI) techniques to small-molecule drug discovery.
Where it might have taken the traditional discovery process 4–5 years to come up with the drug candidate—an A2 receptor antagonist designed to help T cells fight solid tumors—it was found in 8 months by harnessing Exscientia’s ‘Centaur Chemist’ AI design platform. This system can computationally sort through and compare various properties of millions of potential small molecules, looking for 10 or 20 to synthesize, test and optimize in lab experiments before selecting the eventual drug candidate for clinical trials.
Within 3 weeks, Exscientia, a 2012 spinoff of the University of Dundee, UK, announced a $225 million Series D financing round (Table 1), along with a $300 million equity commitment that it can draw on at its discretion. In 2020, the company did much the same, announcing a drug candidate with Sumitomo Dainippon Pharma in Osaka, Japan, then later raising $100 millionin Series C funding. That drug, a selective serotonin reuptake inhibitor (SSRI) designed to treat obsessive compulsive disorder (OCD), and the oncology drug are the first two molecules designed with the help of AI to enter clinical trials, Exscientia claims. The company has also formed drug discovery partnerships with Bristol Myers Squibb (BMS), Sanofi, Bayer, GlaxoSmithKline, Roche and the University of Oxford (Table 2), and is building its own pipeline.
Exscientia is just one of many companies founded in the past decade around AI-based strategies for drug discovery and development, several of which have raised substantial funding recently (Table 1). Some of these are also developing tools to accelerate the identification of small-molecule drug candidates. Others such as Recursion Pharmaceuticals, which recently raised $436 million in its initial public offering, are generating vast amounts of bespoke data on cellular behavior in the hope that these can be mined using AI to reveal biological insights that could inform the discovery of innovative drugs. More established, less health-care-focused tech companies, such as IBM, Microsoft and Google, are getting involved too.
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