AI-developed drug shows potential to slow biological aging

Wednesday 09 - 07:47

By: Azzat Manal

AI-developed drug shows potential to slow biological aging

New clinical data from Insilico Medicine suggest that a drug initially developed to treat a serious lung disease could also influence biological markers associated with aging, opening a new avenue for research into healthy longevity.

The experimental drug, rentosertib, was developed with the help of artificial intelligence and is being investigated as a potential treatment for idiopathic pulmonary fibrosis, a chronic condition in which lung tissue becomes scarred and progressively loses its ability to transfer oxygen efficiently.

A clinical trial conducted last year indicated that rentosertib could improve lung function in patients with idiopathic pulmonary fibrosis. Further analysis of the trial data has now revealed changes in biological aging markers, according to findings published in Nature Biotechnology.

Researchers assessed the participants using six different so-called aging clocks, computational tools that use biological data to estimate a person's biological age and assess how quickly the body may be aging. All six measures indicated a reduction in estimated biological age after patients had received the drug for 12 weeks.

The study involved 43 patients, making the findings potentially significant but still preliminary. Aging clocks rely on different biological indicators related to the condition of cells, tissues and organs, and researchers caution that these tools do not necessarily provide a definitive measure of the aging process itself.

The results have attracted interest because they highlight a growing role for artificial intelligence in biomedical research. AI is increasingly being used not only to identify potential drug candidates but also to analyze large biological datasets and uncover relationships between diseases, proteins, cellular processes and aging.

Insilico Medicine has been developing AI-based approaches to drug discovery for more than a decade. The company, founded in 2014 by Alex Zhavoronkov, has built systems designed to process extensive biological and medical datasets and identify disease-related targets before generating molecules that could potentially interact with them.

The development process behind rentosertib illustrates this approach. Researchers used computational models to study proteins associated with disease and then generate molecular structures designed to interact with specific biological targets. The strategy is intended to accelerate parts of the traditionally lengthy and expensive drug-development process.

In the case of rentosertib, the initial focus was idiopathic pulmonary fibrosis, a potentially life-threatening disease characterized by progressive scarring of the lungs. The drug's possible effects on biological aging emerged as an additional area of interest during the clinical research.

Harvard Medical School professor Vadim Gladyshev, who contributed to the development of one of the aging-clock tools used in the research, described the findings as an important indication that estimated biological age could potentially be reduced. However, he also stressed that the evidence remains far from conclusive because of the small sample size and limitations surrounding biological-age measurements.

Experts say an important unanswered question is whether changes detected by aging clocks actually correspond to slower aging, better health or longer life. A treatment can alter biological markers without necessarily changing the underlying aging process.

Another major limitation is that the drug has so far been studied in patients with idiopathic pulmonary fibrosis rather than healthy individuals. Researchers therefore cannot rule out the possibility that the changes in aging-related markers were linked to the disease or to the treatment's effects on the condition rather than to aging itself.

Eric Topol, a cardiologist and author of “Super Agers,” said the results were promising but emphasized that no definitive trial has yet demonstrated that rentosertib can slow human aging.

The experimental drug also has not received regulatory approval, meaning additional clinical testing will be required before it can be widely used, even for its intended application in lung disease.

Researchers believe the findings nevertheless demonstrate how AI could help create new connections between drug discovery, medicine and aging research. Larger and longer-term clinical trials, particularly those involving healthy people, will be needed to determine whether the reduction in biological-age markers translates into meaningful improvements in health and longevity.