Research News

Feixiong Cheng, PhD, Genomic Medicine Institute, has been awarded a one-year, nearly $325,000 grant from the National Institutes of Health (NIH) to develop artificial intelligence and machine learning tools that can accelerate the drug discovery process for Alzheimer's disease (AD). This award is an administrative supplement to his five-year, $3.3 million grant to develop computational tools to identify effective repurposable drugs for AD.

Currently the leading cause of dementia and sixth leading cause of death in the United States, AD is set to impact approximately 13.8 million Americans by 2050 if effective treatments are not developed. Unfortunately, due to the high attrition rate for AD clinical trials and the complexity of the disease, AD drug discovery remains stunted.

Dr. Cheng's team has found that common underlying mechanisms in neurodegenerative diseases, called endophenotypes, could serve as a foundation for generating actionable targets for drug repurposing in AD. Amyloidosis and tauopathy are endophenotypes in AD, responsible for the buildup of beta amyloid and tau proteins in the brain that lead to amyloid plaques and tau neurofibrillary tangles (two hallmark AD-related brain changes).

With this award, the researchers will design artificial intelligence and machine learning tools that harness existing data to systematically identify and characterize novel underlying AD-related molecular networks and potential risk genes related to amyloidosis and tauopathy endophenotypes.

"Given our preliminary findings, we posit that identifying endophenotype networks shared by amyloid and tau as well as risk genes, more so than mutated genes, will offer unexpected opportunities for drug repurposing and combination therapy design in AD compared to traditional approaches," said Dr. Cheng. "Altogether, successful completion of this project will offer powerful approaches for NIH-funded data analyses as well as druggable targets to advance the development of precision medicine treatments for AD."