Inside the nascent industry of AI-designed drugs. News feature from edbites
“In the last couple of years, AI has gone from being hypothetically interesting to real programs moving towards the clinic,” says Williams-Jones. “There’s no shortcuts to drug discovery. We can have better informed ideas, but you still have to go through the rest of the [development] process.”
Exscientia’s next AI-developed candidate, a small molecule called EXS4318, is not far behind. A selective protein kinase C-theta inhibitor, designed for inflammatory and autoimmune conditions, EXS4318 has been licensed to Bristol Myers Squibb in a partnership, according to a company press release. The company has 16 other AI-designed drugs in its pipeline, including drugs for COVID-19, tuberculosis, malaria, and hypophosphatasia — a rare, inherited disorder that affects bones and teeth.
“This is where AI is going to lead as well. It’s not just about using AI to make drug discovery better, but about how we can create better drugs overall,” Hopkins says.of its phase 1 safety and pharmacokinetics trial of INS018_055, designed by AI for idiopathic pulmonary fibrosis, a progressive disease that causes scarring of the lungs.
Recursion is also working to develop a therapeutic agent for ovarian cancer that targets a gene that their AI systems indicated was part of the same pathway as CDK12, an existing target that has proved challenging to inhibit directly. In preclinical studies that target the CDK12-associated protein, 40% of mice showed a complete response. When the compound was paired with a PARP inhibitor, tumors were eliminated in four out of five mice.
BenevolentAI has also filed a clinical trial application with the UK Medicines and Healthcare Products Regulatory Agency for BEN-8744, a small molecule phosphodiesterase 10 inhibitor designed to treat ulcerative colitis. If approved, Williams-Jones says BenevolentAI plans on beginning a phase 1 trial in the first half of 2023. But for BenevolentAI, as for everyone else, he points out this is still early days.
AI and machine learning took a completely different approach. “Machine learning is based on the results you attain rather than a statistical model that describes the population,” Deane says. “It’s about finding predictive patterns in the data.”
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