NEW YORK: Researchers have developed a method based on Artificial Intelligence (AI) that rapidly identifies currently available medications that may treat 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. Importantly, 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 researcher Artem Sokolov from Harvard Medical School.
"We therefore built a framework for prioritising drugs, helping clinical studies to focus on the most promising ones," Sokolov added.
For the study, published in Nature Communications, the team described their framework, called DRIAD (Drug Repurposing In Alzheimer's Disease), which relies on machine learning — a branch of artificial intelligence in which systems are "trained" on vast amounts of data, "learn" to identify telltale patterns and augment 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. (IANS)