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AI reveals current drugs that may help combat Alzheimer’s disease. Team at Harvard Medical School and Massachusetts General Hospital has developed an artificial intelligence-based method to screen currently available medications as possible treatments for Alzheimer’s disease.
The method could represent a rapid and inexpensive way to repurpose existing therapies into new treatments for this progressive, debilitating neurodegenerative condition. It could also help reveal new, unexplored targets for therapy by pointing to mechanisms of drug action.
“Repurposing FDA-approved drugs for Alzheimer’s disease is an attractive idea that can help accelerate the arrival of effective treatment, but unfortunately, even for previously approved drugs, clinical trials require substantial resources, making it impossible to evaluate every drug in patients with Alzheimer’s disease,” said Artem Sokolov, HMS instructor in biomedical informatics in the Blavatnik Institute and director of informatics and modeling in the Laboratory of Systems Pharmacology at HMS. “We therefore built a framework for prioritizing drugs, helping clinical studies to focus on the most promising ones.”
In an article published on Feb. 15 in Nature Communications, Sokolov and colleagues describe their framework, called DRIAD, or Drug Repurposing In AD, which relies on machine learning, a branch of artificial intelligence in which systems are “trained” on vast amounts of data and “learn” to identify telltale patterns, augmenting researchers’ and clinicians’ decision-making.
DRIAD works by measuring what happens to human brain neural cells when treated with a drug. The method then determines whether the changes induced by a drug correlate with molecular markers of disease severity.
The approach also allowed the researchers to identify drugs that had protective as well as damaging effects on brain cells.
By Аvera Allen | Linkedin
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