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AI algorithms find three drugs that could combat aging

Jun. 15, 2023.
1 min. read Interactions

Algorithms were trained on already-published data, making them cost-effective

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Amara Angelica

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Amara Angelica is Senior Editor, Mindplex

Cellular senescence (credit: University of Edinburgh)

Three “senolytics”—compounds in drugs that could help stave off the effects of aging (such as cancer, type-2 diabetes, osteoarthritis and viral infection)—have been discovered by researchers at the University of Edinburgh.

These algorithms were trained on already-published data, making them cost-effective, the researchers note.

Lab tests in human cells revealed that three of the compounds—ginkgetin, periplocin and oleandri—were able to remove senescent* cells without damaging healthy cells.

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

*Cellular senescence is “a stress response involved in aging and diverse disease processes, including cancer, type-2 diabetes, osteoarthritis and viral infection,” the researchers explain.

Citation: Quintanilla, A., Elliott, R. J., Dawson, J. C., Sun, J., Campa, V. M., Carragher, N. O., Acosta, J. C., & Oyarzún, D. A. (2023). Discovery of senolytics using machine learning. Nature Communications, 14(1), 1-15. https://doi.org/10.1038/s41467-023-39120-1 (open-access)

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One thought on “AI algorithms find three drugs that could combat aging

  1. Identifying promising compounds found in natural products, as well as their precise impact mechanism, is a wonderful yet obvious application domain of new emerging AI tools. Hope and expect to see much more of these in the near future. Low hanging fruits in the field of medicine.
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