AI designed, synthesised and validated new drug in 46 days

A company developing artificial intelligence (AI) for drug discovery has published a paper describing how an AI system designed six novel inhibitors of DDR1, a kinase target implicated in fibrosis and other diseases, in 21 days. Insilico Medicine, US, who conducted the study, developed the Generative Tensorial Reinforcement Learning (GENTRL) AI. Four of the compounds were found to be active in biochemical assays and two were validated in cell-based assays. One lead candidate was tested and demonstrated favourable pharmacokinetics in mice. After the design stage, GENTRL was able to synthesise and pre-clinically validate the drug in 25 days, making the whole process take 46 days. According to the research team, the method is 15 times faster than a typical pharma company’s efficient R&D process. Specialised algorithms created synthetic datasets indistinguishable from real datasets by having two neural networks compete against each other. One neural network generates the data and the other compares it to a real data set in iterative cycles so that the degree of error in the synthetic data set is gradually decreased. Rather than using trial and error when looking for molecular leads, requests are made to the network to generate specific leads and leads are generated on demand.

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