AI Helps Identify Possible Alzheimer’s Treatments

Researchers at Massachusetts General Hospital developed an artificial intelligence (AI) that quickly identifies drugs currently available that might treat Alzheimer’s disease. It also can point to potential new drug targets. The framework is called Drug Repurposing In Alzheimer’s Disease (DRIAD), and depends upon machine learning, where systems are trained on huge amounts of data to learn to identify patterns. They published their research in Nature Communications.

“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, director of Informatics and Modeling at the Laboratory of Systems Pharmacology at Harvard Medical School (HMS). “We therefore built a framework for prioritizing drugs, helping clinical studies to focus on the most promising ones.”

DRIAD measures what happens to human brain neural cells when treated with a drug. The AI determined if the changes caused by the drug are associated with molecular markers of disease severity. It can also examine which proteins are targeted by the most promising molecules and determine common trends among the targets. The researchers applied the AI to 80 FDA-approved and clinically tested drugs across a broad range of indications. The AI came up with a ranked list of candidates, with the top spots anti-inflammatory drugs used to treat rheumatoid arthritis and blood cancers. They all are JAK inhibitors (Janus kinase inhibitors), which block the action of inflammation-driving Janus kinase proteins, which are known to be associated with autoimmune disease, and are suspected of playing a role in Alzheimer’s.

Mar 12, 2021

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