UVA Health develops artificial intelligence tool
May 2025
UVA’s biomedical engineer Jeffrey Saucerman, Ph.D., left, and Ph.D. student Taylor Eggertsen, right, created a drug-screening tool that helps speed up the creation of new disease treatments. (courtesy UVA Health)
story courtesy of UVA Health
Scientists at the University of Virginia School of Medicine have developed a computational tool to speed up the creation of new disease treatments. This tool surpasses current artificial intelligence methods by pinpointing which patient populations might benefit and how the drugs function within cells. The researchers have showcased the new tool’s potential by identifying a promising candidate to prevent heart failure, a leading cause of death in the U.S. and worldwide.
The new AI tool, LogiRx, can predict how drugs will affect biological processes in the body, assisting scientists in understanding the effects drugs may have beyond their original purpose. For instance, researchers discovered that the antidepressant escitalopram, marketed as Lexapro, could prevent harmful changes in the heart that lead to heart failure, a condition responsible for nearly half of all cardiovascular deaths in the U.S.
“AI needs to move from detecting patterns to generating understanding,” says UVA’s Jeffrey J. Saucerman, Ph.D. “Our LogiRx tool helps us identify not just which drugs can be repurposed for heart disease, but how they work in the heart.”
PREVENTING HEART FAILURE
Heart failure kills more than 400,000 Americans every year. One of its hallmarks is the overgrowth of cells that thicken the heart muscle and prevent the organ from pumping blood as it should. This is known as cardiac hypertrophy.
Saucerman and his team, led by Ph.D. student Taylor Eggertsen, aimed to see if LogiRx could identify drugs capable of preventing cardiac hypertrophy and counteracting heart failure. They utilized the tool to assess 62 drugs previously identified as promising candidates for this task. LogiRx successfully predicted “off-target” effects for seven of these drugs that could assist in preventing harmful cellular hypertrophy, which were confirmed in cells for two of the drugs.
The scientists then evaluated LogiRx’s predictions by doing lab tests and by looking at outcomes in patients taking the drugs. The latter revealed that patients taking escitalopram were significantly less likely to develop cardiac hypertrophy. “LogiRx identifies unexpected new uses for old drugs that are already shown to be safe in humans,” says Eggertsen, in UVA’s Department of Biomedical Engineering, a joint program of the School of Medicine and School of Engineering. “This tool can help researchers explore new patient populations that could benefit from a drug or to avoid unwanted side effects.”
Further laboratory research and clinical trials are required before doctors can begin prescribing escitalopram for heart health. However, Saucerman is enthusiastic about the potential of LogiRx to advance and expedite new treatments not only for cardiac hypertrophy but also for a variety of other serious medical conditions.
“AI is accelerating many aspects of drug development, but it has made less progress in providing the required understanding of how these drugs work in the body,” Saucerman says. “LogiRx is a step toward combining AI with existing knowledge of how cells work to find new uses for old drugs.”
An artificial intelligence tool developed at the UVA School of Medicine may soon be able to save lives. (courtesy UVA Health)