A groundbreaking study published in Nature has revealed early findings suggesting that a drug called rentosertib, initially created to treat idiopathic pulmonary fibrosis, may also have potential in slowing the ageing process. Developed by Insilico Medicine with the aid of artificial intelligence (AI), the drug appears to be making strides not only in respiratory health but possibly in longevity as well.
:max_bytes(150000):strip_icc():format(jpeg)/rentosertib-drug-090826-23fdd4d75f534cf1bd826a106b437582.jpg)
Rentosertib is highlighted as a potentially pioneering small molecule devised through generative AI methods. Its development process has been likened to “scanning a lock and generating a key that fits the lock,” as described by Dr. Alex Zhavoronkov, founder of Insilico Medicine. This innovative approach aims to enhance the efficiency of drug discovery by leveraging the capabilities of AI technology.
Initially intended to address chronic lung diseases, clinical trials concerning rentosertib’s effectiveness have shown significant improvement in lung function. Remarkably, these trials have also provided evidence suggesting the drug might slow some principal markers of biological ageing. The dual findings have sparked interest in further exploring the drug’s applications in both pulmonary care and age-related health issues.
To investigate the potential of rentosertib in influencing biological age, researchers employed six different AI tools, termed “aging clocks”. These clocks function as measurement systems for assessing biological age through various markers, rather than solely relying on chronological age. Unique to this study were the proteomic clocks used, which are designed to more accurately quantify biological changes.
Participants in the clinical trial included 42 individuals—men and women over the age of 40, recruited from 21 sites across China. Their biological age was scrutinised both prior to and following a 12-week treatment course with rentosertib, analysing data from all six aging clocks, which included four chronological and two mortality-based clocks.
Encouragingly, the results indicated a consistent reduction in biological age among those who received rentosertib, in stark contrast to the placebo group that demonstrated either minimal changes or slight increases in biological age. Such findings may point to the drug’s significant impact on biological ageing and further support its exploration for longevity benefits.
Despite the exciting results, experts have urged caution regarding the study’s implications. Vadim Gladyshev, a professor at Harvard Medical School who contributed to developing one of the ageing clocks, stressed the necessity for a measured interpretation of the findings. He noted that AI tools are not infallible and that the study’s relatively small sample size limits the scope for definitive conclusions.
Nonetheless, Gladyshev acknowledges this research as a pioneering contribution to the understanding of biological age reduction. He remarked, “This is the first study that shows, very clearly, that predicted biological age can be reduced,” indicating that the findings could pave the way for further investigations in the fields of gerontology and longevity.
In light of these findings, the study presents a promising avenue of exploration for future research aimed at understanding and potentially mitigating the effects of ageing. With continued advancements in AI-assisted drug development, there is growing optimism about uncovering new interventions that may significantly alter the course of age-related health decline.
As the scientific community delves deeper into the implications of this research, it remains essential to continue rigorous testing and validation of the drug’s effects on larger and more diverse populations. The hope is that rentosertib and similar compounds might contribute to a healthier, longer lifespan for individuals around the globe in the years to come.