In the study conducted by researchers of The University of Edinburgh, A trio of chemicals that target faulty cells linked to a range of age-related conditions were found using the pioneering method, which is hundreds of times cheaper than standard screening methods.

Findings suggest that the drugs can safely remove defective cells – known as senescent cells – linked to conditions including cancer, Alzheimer’s disease and declines in eyesight and mobility.

Harmful side-effects
While previous studies have shown early promise, until now few chemicals that can safely eliminate senescent cells have been identified. These senolytic drugs are often highly toxic against normal, healthy cells in the body.

Machine learning
A team led by Edinburgh researchers has devised a new  way of discovering senolytic drugs using AI.

They developed a machine learning model by training it to recognise the key features of chemicals with senolytic activity, using data from more than 2,500 chemical structures mined from previous studies.

The team then used the models to screen more than 4,000 chemicals, identifying 21 potential drug candidates for experimental testing.

This study demonstrates that AI can be incredibly effective in helping to identify new drug candidates, particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets.

Natural products
Lab tests in human cells revealed that three of the chemicals – called ginkgetin, periplocin and oleandrin – were able to remove senescent cells without damaging healthy cells.

All three chemicals are natural products found in traditional herbal medicines. Oleandrin was found to be more effective than the best-performing known senolytic drug of its kind.

Source:https://www.ed.ac.uk/news/2023/ai-algorithms-find-drugs-that-could-combat-ageing