A new analysis of blood samples from a 42-patient trial shows that rentosertib, a drug designed by AI for idiopathic pulmonary fibrosis, appears to reverse markers of biological aging by up to six years.
Insilico Medicine, an AI-driven pharma company, reports these findings. The drug was originally built to treat IPF, a condition that scars lung tissue. A trial last year demonstrated improved lung function and collected the blood data now being studied. The results appear in Nature Biotechnology.
Six independent aging clocks point the same way
Aging clocks are AI models that predict biological age from blood proteins. Researchers ran six of them on the patient data. These models were 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. This does not mean patients actually got measurably younger. It only means 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). This suggests 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. 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 is 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 is 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.
What it means
For people making things, this does not change how they work. The drug targets a specific disease, not general aging. Patients with IPF might see better lung function and protein patterns that look younger. But no one should assume this means a fountain of youth is near. The study is small, limited to sick patients, and relies on models rather than direct measurement of age. The takeaway is cautious optimism for a specific treatment, not a universal solution.
