Researchers at Case Western Reserve University have received a $6.2 million, five-year grant from the National Institute on Aging to apply artificial intelligence and machine learning to the search for genetic targets in Alzheimer's disease. The principal investigator is Jonathan L. Haines, who chairs the Department of Population and Quantitative Health Sciences at the Case Western Reserve School of Medicine.
The goal, according to Haines, is to hand physicians and drug developers new information that could be used to prevent, slow or potentially cure the disease. That framing points to a gap in the current treatment landscape rather than an incremental improvement on it.
Alzheimer's drugs approved by the U.S. Food and Drug Administration work by clearing amyloid plaques, the abnormal protein clusters that accumulate between neurons and interfere with communication between brain cells. Those medications can slow cognitive decline in people with mild disease, but they carry serious side effects and leave the underlying causes of Alzheimer's untouched.
Genetics offers a different entry point. If computational methods can pinpoint which genes drive the disease process, the resulting targets could support therapies aimed at the biology behind the plaques rather than the plaques themselves. That work is just beginning under this grant, and the five-year timeline is a reminder that any resulting treatments would be years further down the road.