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How We're Leveraging AI to Address Key Pain Points in Drug Discovery -- Najat Khan, PhD on Bloomberg

Speaking to Bloomberg Radio, Chief R&D and Chief Commercial Officer Najat Khan, PhD shared how Recursion is directly addressing the pain points that lead to failures in the clinic through AI-enabled Maps of Biology. On Recursion’s AI-enabled approach. “What Recursion is doing is leveraging AI and high-quality data that is generated in our own labs at scale” to build AI algorithms that are used to “really understand what is driving the disease.” Then, “we use generative AI to design molecules that someone –even a PhD organic chemist – never considered before.” On using AI to improve the speed and efficiency with which we produce first-in-class molecules. Traditionally, “It takes 42-50 months to get into the clinic.” Recursion's REC-1245 RBM39 degrader for solid tumors and lymphoma “took 18 months” with “less than 200 molecules synthesized. Usually in industry – and I come from large pharma – you’re making 3,000, 4,000, 5,000 compounds. So we’re doing things better, faster, and the insights are a first-in-class molecule, which means nobody has come up with this before.” On the importance of high-quality, proprietary data. “Even before we talk about AI, data is the differentiator. And fit-for-purpose datasets. At Recursion, we have around 60 petabytes of data…It’s having a wet lab and dry lab. Generating data, using the data to train your algorithms, and those algorithms are predicting which experiments you should make.” With Maps of Biology, we’re able to understand “not just what’s driving the disease, but everything that’s connected to it. Think of it as the highways that connect across our different cells and organs.”