A pharmaceutical company claims to have used artificial intelligence to discover a drug that reverses the impacts of aging. The finding highlights how the technology could make the drug discovery process easier or at least faster.
Beating the ‘aging clocks’ Last year, Insilico Medicine, a company that “aims to accelerate drug discovery” using artificial intelligence, announced that a clinical trial of one of its drug candidates suggested AI could help treat a chronic lung disease, said The New York Times. The disease, idiopathic pulmonary fibrosis, or IPF, is sometimes referred to as Alzheimer’s of the lungs. Now, new data from the same clinical trial shows an even “more intriguing possibility”: The drug, called rentosertib, could “also slow the aging process.”
The company used AI to assist in generating rentosertib’s molecular structure. The drug may be capable of reducing the biological markers of age as measured by six separate “aging clocks,” or AI technology “designed to predict a person’s morbidity and mortality,” said a new study published in the journal Nature Biotechnology,
‘Not replacing scientific intuition’ The results of this study are the first to show “very clearly” that “predicted biological age can be reduced,” said Vadim Gladyshev, a Harvard Medical School professor who helped build one of the aging clocks, to the Times. Still, Gladyshev acknowledges that the study is far from conclusive, citing the small sample size and the unreliability of aging clocks.
Most notably, Insilico’s drug has “not yet been tested in healthy patients,” said the Times. Because the company conducted its clinical trial solely with IPF patients, the results may be specific to this condition.
The idea of “reducing aging” has become the “obsession of some tech bro-types,” but the “actual utility of aging clocks is up for debate,” said Gizmodo. While some researchers believe that such “catch-all measurements” could be useful, there’s still a “long way to go before they become truly meaningful markers.”
AI is not “replacing scientific intuition,” and it’s “unlikely to do so anytime soon,” said Forbes. But it can “make the costly time-consuming R&D work” of preparing for clinical trials “more efficient.”
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