NIH awards Cedars-Sinai $8M for AI-based Alzheimer's research

Cedars-Sinai’s department of computational biomedicine has been awarded an $8 million NIH grant to use artificial intelligence methods to identify genetic predictors of Alzheimer's disease.

According to the Alzheimer's Association, more than 6 million Americans are currently living with Alzheimer’s disease, with that number expected to triple by 2050.

“Our goal is to really democratize AI, so that absolutely anybody could use this technology,” Jason H. Moore, PhD, chair of Cedar-Sinai’s department of computational biomedicine and lead author of the AI-based research, said in a release from the hospital.

“There have been very few new FDA-approved and effective drugs for Alzheimer’s disease over the past 20 or 30 years,” he said. “That’s something I have in mind all the time—that everything we do ultimately leads to new knowledge, new results that could potentially inform the development of new lifesaving drugs.”

The center of the research project will revolve around software, developed by Moore, that uses machine learning to help experts analyze data. Named “Aliro,” the software can provide researchers with insights and analysis from large data sets. The software learns from experience and stores results in a database and can use stored information to recommend further analysis.

“That’s kind of what our system is doing,” Moore said. “It’s recommending the next best machine learning analysis and then doing it automatically and generating the results.”

Moore reports collecting information from more than 20 databases on genes, drugs, diseases and biochemical pathways.

“The key research question I’m addressing in this grant is not only how we get artificial intelligence to automate the machine learning, but also how we get it to use all of this knowledge we have about Alzheimer’s disease, to focus the analysis, choose the right variables, interpret models and make sense out of them,” Moore said.