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New approach that uses machine learning could transform drug development Writing in the July 12, 2021 online issue of Nature Communications, researchers at University of California San Diego School of Medicine describe a new approach that uses machine learning to hunt for disease targets and then predicts whether a drug is likely to receive FDA approval. The study findings could measurably change how researchers sift through big data to find meaningful information with significant benefit to patients, the pharmaceutical industry and the nation s health care systems. Academic labs and pharmaceutical and biotech companies have access to unlimited amounts of big data and better tools than ever to analyze such data. However, despite these incredible advances in technology, the success rates in drug discovery are lower today than in the 1970s.

San diegoUnited statesUniversity of california san diegoPradipta ghoshSoumita dasDebashis sahooEmily hendersonNature communicationsDepartment of pathologyUc san diego institute for network medicineResearch excellenceUc san diego school of medicineCalifornia san diego schoolMolecular medicineDiego schoolDiego institute