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Artificial intelligence programs reviewed tens of thousands of human drug studies, found a pattern tied to success, and proposed a lung cancer design later taken up by a manufacturer.

Human genetics is reshaping drug discovery by revealing reliable targets, improving success rates, and reducing costly clinical failures in the development of safer, more effective treatments.

Rentosertib, built with generative AI for scarred lungs, starts a year-long study after protein clocks suggested treated patients looked biologically younger.

Six independent protein-based aging clocks moved younger in forty-two patients with idiopathic pulmonary fibrosis, with the strongest signal at four weeks on a mid-range dose.

A custom treatment built from each patient's tumor mutations, given with an existing immunotherapy, met its main goals in a large late-stage study and relies on computational ranking of targets.

InnoCare's TYK2 inhibitor soficitinib hits vitiligo Phase 2 endpoint, advancing to Phase 3. Competitive autoimmune skin disorder trial shows strong F-VASI improvement.

Scientists designed CRISPR to self-destruct tumor cells carrying p53 mutations, a target no drug has ever reached. A Nature paper details the approach for ovarian, pancreatic, and lung cancers.

AI-driven drug discovery fueled 26 novel FDA therapy approvals in early 2026, delivering breakthrough cancer treatments and first-ever options for rare neurological disorders.