An AI-designed drug for chronic lung disease dramatically reversed the markers of biological aging in its first clinical trials. In a clinical trial published in Nature Biotechnology, scientists evaluating the drug rentosertib — developed by generative artificial intelligence for idiopathic pulmonary fibrosis (IPF) — discovered it also significantly lowered biological age. Evaluating blood-protein samples from 42 trial participants across six independent 'proteomic aging clocks,' the researchers observed a consistent shift toward younger biological profiles, with some models estimating a decline in biological age of up to several years. In contrast, patients receiving a placebo showed virtually no change or even slight increases in their biological aging markers over the 12-week study. While these results are highly promising, researchers caution that they are still preliminary. Because idiopathic pulmonary fibrosis is an age-related illness characterized by severe tissue damage and inflammation, it remains unclear whether rentosertib directly targets the aging process itself or if treating the underlying lung disease simply altered the specific blood proteins tracked by the aging clocks. Furthermore, because the trial was small and lasted only three months, scientists emphasize that larger, longer-term clinical studies are required to verify if these biological age reversals translate to lasting, tangible health benefits for patients. source: Insilico Medicine. (2026). Integration of proteomic aging clocks in a phase 2a clinical trial of rentosertib. Nature Biotechnology.

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NEW - Anthropic CEO Dario Amodei says their Claude AI model has led to the discovery of a “new molecular machine” capable of gene editing

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The CEO of Anthropic said Saturday the artificial-intelligence industry should slow its fast-moving development to give safety measures time to catch up. Without it, Dario Amodei warned AI could be capable within six to 12 months of leading a swarm that could take over the entire internet, among other risks. to.pbs.org/4irqqd0

An AI system trained on more than 20,000 protein structures from pharmaceutical companies outperforms AlphaFold-like models that use only public data go.nature.com/4gTSLaA