Researchers from Case Western Reserve University School of Medicine and collaborators have received a five-year, $2.8 million grant from the National Institute on Aging to identify FDA-approved medications that could be repurposed to treat Alzheimer's disease.
The award enables the researchers to develop computer algorithms that search existing drug databases, and to test the most promising drug candidates using patient electronic health records and Alzheimer's disease mouse models.
Rong Xu, a principal investigator on the new award and associate professor of biomedical informatics in the department of population and quantitative health sciences at Case Western Reserve University School of Medicine. The project builds on Xu's work developing already helped researchers identify new indications for old drugs.
"We will use Drug Predict, but the scope of this project is much more ambitious," Xu said. Xu plans to develop new algorithms as well as apply Drug Predict to Alzheimer's, building a publicly available database of putative Alzheimer's drugs in the process. The database will include drugs that have potentially beneficial mechanisms of action and that are highly likely to cross the blood-brain barrier.
The blood-brain barrier has been a major obstacle in drug discovery for brain disorders, including Alzheimer's disease. The protective membrane surrounds the brain to keep out foreign objects like microbes but can also keep out beneficial drugs. "Finding drugs that can pass the blood-brain barrier is the 'holy grail' for neurological drug discovery," Xu said.
In addition, "With this award, we will develop novel machine-learning and artificial intelligence algorithms to predict whether chemicals can pass the blood-brain barrier and whether they may be effective in treating Alzheimer's disease."
The research team will work with Xu's research group to validate repurposed candidate drugs with computer-simulated clinical trials, involving electronic health records from more than 53 million patients nationwide. The team study the most promising drug candidates in mice genetically modified to have Alzheimer's-like disease.
The new award could lead to human studies testing alternative medications for Alzheimer's disease. "The unique and powerful strength of our project is our ability to seamlessly combine novel computational predictions, clinical corroboration, and experimental testing," Xu said.
This approach allows researchers to rapidly identify innovative drug candidates that may work in real-world Alzheimer's disease patients. Researchers anticipate the findings could then be expeditiously translated into clinical trials.