Beyond the Skin – Can AI Reverse Biological Ageing? 

By Dáire McConville

In a world now filled with the lust and desire for more youthful skin, slimming appearances, and perfect faces, the ageing process taking place beneath the surface is often overlooked. From Botox to Ozempic, face lifts to ‘Turkey teeth’, it’s clear to see that these features are more prevalent in society than ever before. But what about our actual physical health, body and mind; feeling good long-term, rather than a temporary fix. Now with the use of artificial intelligence taking over many industries and platforms, it comes as no surprise that the AI model has fast made its way to the drug market.   

Rentosertib is a newly researched AI drug that has initially been designed to treat a chronic lung condition, yet in clinical testing has been proven to slow the biological aging process. Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease in which the lung tissue thickens and hardens, negatively impacting the lungs’ role in delivering oxygen to the bloodstream. A disease with a largely unknown onset, it is often very difficult to treat and therefore has a high risk of death associated a few years after being diagnosed. ^[1] With a prevalence rate of 27.2 per 100,000, North America has the highest rate in comparison to Europe or Asia with respective 14.6 and 14.8 per 100,000. ^[2] As a result, US pharmaceutical company Insilico Medicine coined the AI model with the aim of reducing the disease.  

Rentosertib’s initial aim was to pinpoint specific proteins involved in the development of the disease. The AI model analyzed thousands of medical records, medical data from blood tests along with the functions and effects specific proteins have on disease recovery. This isn’t just a ChatGPT or Claude AI tool, but rather a specific computational system that was designed to identify disease-related proteins and novel molecules capable of blocking their activity- an approach that ultimately led to the development of Lentosetib, otherwise known as Rentosertib. ^[1] 

So, where does the antiaging process come into all of this? During clinical trials, the drug was shown to slow some of the major aspects of biological aging. Researchers used 6 different ‘aging clocks’ to try support their study. Proteomic clocks (mathematical models that estimate an individual’s biological age by analyzing patterns of proteins in the blood or tissue), where used to examine both behavioral and environmental effects that impact aging. As the drug primarily affects individuals above the age of 60, the trial involved 71 IPF patients, both male and female aged over 40 across 21 different locations in China, over a 12-week period.  

The patients were placed into smaller groups, with each group receiving a different dosage level, either once daily at 30mg, twice daily at 30mg, once daily at 60mg or were given a placebo. The analysis showed in the groups receiving the Lentosetib drug, biological aging across all 6 aging clocks decreased compared with pre-treatment levels, and that the placebo group showed little to no change in biological age, a promising result for a significant breakthrough.  

However, Lentosetib represents just one example of a much wider shift towards the use of AI in drug discovery. Closer to home, researchers at Queen’s University Belfast are also exploring the potential. The university is at the forefront of applying AI and machine learning to the processes that govern life. By combining expertise in AI, bioinformatics and clinical science, Queen’s researchers are developing automated drug discovery pipelines to identify and optimize potential drug candidates, with the aim of reducing time and cost associated with traditional drug discovery routes, making medication more accessible and affordable to all. Professor Ian Styles, QUB has stated ‘Artificial intelligence has the potential to revolutionize medicine, and our work at Queen’s is focused on developing new AI technologies to improve our understanding of life and generate data-driven hypotheses that provide new lenses through which to understand our health’. 

So, with the newly developed market that utilizes artificial intelligence, there is also a large ongoing debate about the accuracy of these developed drugs. We have seen the many mistakes AI can make in our everyday life, so should we be trusting it to help save our lives and treat our illnesses? Vadim Gladyshev of the University of Harvard has made it clear that ‘aging clocks are not always reliable’. ^[1] 

References 

Image- https://www.expert.ai/blog/the-ai-opportunity-for-drug-discovery/  

[1]- https://www.dongascience.com/en/news/79816  

[2]- https://pmc.ncbi.nlm.nih.gov/articles/PMC12330001/  

[3]- https://link.springer.com/article/10.1186/s13059-026-04220-w