Scientists at the University of Virginia School of Medicine unveil an AI tool named LogiRx that accelerates the development of disease treatments by predicting how drugs affect cellular processes.
University of Virginia School of Medicine scientists have developed an advanced computational tool called LogiRx, designed to accelerate the creation of new disease treatments. Unlike existing artificial intelligence (AI) approaches, LogiRx delves deeper by identifying not only which patient populations can benefit from certain drugs but also how these drugs interact within human cells.
This breakthrough has already demonstrated its potential by pinpointing a promising drug candidate for the prevention of heart failure, a leading cause of death both in the United States and globally. LogiRx can predict how drugs will influence biological processes in the body, thereby aiding researchers in understanding the broader impacts of medications beyond their primary use.
The team discovered that the antidepressant escitalopram (commercially known as Lexapro) could prevent detrimental changes in the heart that lead to heart failure.
“AI needs to move from detecting patterns to generating understanding,” UVA’s Jeffrey J. Saucerman said in a press release. “Our LogiRx tool helps us identify not just which drugs can be repurposed for heart disease but how they work in the heart.”
Heart failure claims the lives of over 400,000 Americans annually and is characterized by cardiac hypertrophy, an overgrowth of cells that thickens the heart muscle, thus impairing its ability to pump blood effectively.
Saucerman’s team, led by Taylor Eggertsen, a doctoral student in UVA’s Department of Biomedical Engineering, a collaboration between the School of Medicine and School of Engineering, applied LogiRx to evaluate 62 previously identified drugs for their potential to combat cardiac hypertrophy. The tool successfully predicted beneficial ‘off-target’ effects for seven of these drugs, with further confirmation for two via cellular tests.
The efficacy of LogiRx’s predictions was further validated through lab tests and patient data analysis. Remarkably, patients on escitalopram displayed a significantly lower likelihood of developing cardiac hypertrophy.
“LogiRx identifies unexpected new uses for old drugs that are already shown to be safe in humans,” added Eggertsen. “This tool can help researchers explore new patient populations that could benefit from a drug or to avoid unwanted side effects.”
While additional laboratory research and clinical trials are necessary before escitalopram can be prescribed for heart health, Saucerman is optimistic about LogiRx’s potential to advance medical treatments for various serious 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 added. “LogiRx is a step towards combining AI with existing knowledge of how cells work to find new uses for old drugs.”
The team’s findings have been published in the Proceedings of the National Academy of Sciences (PNAS).
Source: UVA Health