AI-driven pharma company Insilico Medicine reports that one of its AI-designed drug candidates shows signs of reversing markers of biological aging.

The drug, rentosertib, was originally developed for patients with idiopathic pulmonary fibrosis (IPF), a disease that scars lung tissue. A trial last year with 42 patients showed improved lung function, and the researchers collected blood samples for protein analysis along the way. That data now forms the basis of a new analysis published in Nature Biotechnology.

Six independent aging clocks point the same way

Aging clocks are AI models that predict a body’s biological age from blood proteins. The researchers ran six of them on the patient data, built by independent teams at Harvard, Oxford, Beijing, and Insilico itself.

All six predicted a lower biological age for treated patients than for those on placebo. The strongest effect was a drop of three to four years by week 4, with one clock showing as much as six years. That doesn’t mean patients actually got measurably younger, only that their blood protein patterns shifted in ways the models read as a younger biological age.

“What convinces me is not the size of the effect but the agreement, because these models share neither their features nor their training data,” says Nobel laureate in chemistry Michael Levitt in a company press release.

The blood values might only look younger because the lungs work better and the body is under less overall strain. But the dose that helped the lungs most (60 mg once daily) differed from the one that cut predicted biological age the most (30 mg twice daily), suggesting an effect at least partly independent of lung function. The researchers also compared treated patients’ blood proteins against more than 55,000 profiles from the UK Biobank, a database that tracks how certain proteins typically change with age. According to the company, rentosertib reversed exactly those changes. These correlations are no proof, obviously, but it shows the “potential,” as the company puts it.

Even so, the study falls well short of settling the question. “This drug looks encouraging,” cardiologist Eric Topol, who is deeply invested in longevity, told the New York Times. “But we do not yet have a definitive trial to make the final judgment.” Vadim Gladyshev of Harvard Medical School points to the small sample size and the fact that biological clocks aren’t always reliable. He still told the Times the study is “the first study that shows, very clearly, that predicted biological age can be reduced.” What’s missing, he says, is a trial in healthy people, since the results may only apply to patients with the lung disease.

AI found the target and designed the molecule

Insilico used two AI systems to develop the drug candidate. One combs through health data and scientific literature for disease-relevant proteins, while the other analyzes their structure and generates matching molecules.

That’s how Insilico landed on the protein TNIK as a target for both aging and pulmonary fibrosis. Going from target protein to drug candidate took about 18 months, and rentosertib is now in a Phase III trial for IPF, the final clinical stage before potential approval.

Insilico Medicine, founded in Hong Kong in 2014, aims to speed up drug development with generative AI. Pharma giant Eli Lilly recently invested in the publicly traded company to bring drugs co-developed with AI to market. Founder and CEO Alex Zhavoronkov says Insilico has developed at least 28 drug candidates with generative AI as of March 2026, many of them now in clinical trials.