The study utilized Phase 2a trial data to test the drug against six distinct proteomic aging clocks—machine learning algorithms that measure the functional health of organs and cells rather than chronological years. Across all six models, researchers from institutions including Harvard, Stanford, and the Broad Institute observed a consistent reduction in the biological age of treated patients.

While these results offer a new blueprint for longevity research, they remain preliminary. Insilico acknowledged that confirming the drug’s efficacy in slowing aging requires broader trials involving healthy volunteers. The company is currently conducting Phase 3 testing for rentosertib specifically as a treatment for pulmonary fibrosis in China, following a 12-week trial that showed improvements in patient lung function. This development highlights the growing ambition of AI-driven drug discovery to target aging and disease simultaneously, though the industry remains cautious given recent clinical failures in other experimental pipelines.