We then tested these drug candidates on two types of cells: healthy and senescent. The results showed that out of the 21 compounds, three (periplocin, oleandrin and ginkgetin) were able to eliminate senescent cells, while keeping most of the normal cells alive. These new senolytics then underwent further testing to learn more about how they work in the body.

More detailed biological experiments showed that, out of the three drugs, oleandrin was more effective than the best-performing known senolytic drug of its kind.

The potential repercussions of this interdisciplinary approach – involving data scientists, chemists and biologists – are huge. Given enough high-quality data, AI models can accelerate the amazing work that chemists and biologists do to find treatments and cures for diseases – especially those of unmet need.

Having validated them in senescent cells, we are now testing the three candidate senolytics in human lung tissue. We hope to report our next results in two years’ time.

I’m really looking forward to seeing how this approach develops,