Many seniors are now using artificial intelligence to help manage their medication plans, but soon AI could be used to identify or discover the drugs themselves.
One machine learning tool was found to successfully identify new anti-aging drugs, a team of researchers at Edinburgh University recently announced.
The findings suggest that AI, if accurate, could identify new drug chemicals more cheaply and efficiently than current methods.
AI drug discovery is a burgeoning field, and now more than a dozen AI-designed drugs have begun to enter clinical trials, Nature Medicine wrote last month.
Some of the ways AI can help discover drugs is through analyzing data sets faster than humans can, predicting key chemical properties, or offering improved ranking techniques.
Senolytic drugs, for example, combat aging by removing senescent cells, which play a major role in aging and age-related health decline. By destroying these cells, the drugs could potentially delay or alleviate a number of conditions including cancer, cardiovascular disease and dementia.
Unfortunately, most senolytic candidates are highly toxic and destroy normal, healthy cells too.
Using data from previous studies, Edinburgh researchers trained their AI model to screen chemicals from among 4,000 potential options that could be safe for senolytic activity.
After 21 initial candidates were identified, the chemicals were tested in labs and found that three chemicals — ginkgetin, periplocin and oleandrin — could remove senescent cells without damaging healthy cells, the researchers said.
In the immediate future, AI will continue to be used to help with medication in other ways. One example is DrFirst’s tool, which can streamline refill and renewal requests. The latter can help on the provider side by reducing clinician burnout and even flag prescription mistakes, McKnight’s reported.
