AI-Powered Computational Tool Shows Promise in Identifying How Drugs Affect Cells in the Body

A study published in PNAS has showed that a computational tool that identifies how drugs work inside cells may help identify candidates to treat certain conditions.

The tool, developed by researchers at UVA, was able to identify a “promising candidate to prevent heart failure” – Lexapro. The tool is called LogiRx and is powered by AI to “predict how drugs will affect biological processes in the body, helping scientists understand the effects the drugs will have other than their original purpose.” It showed that Lexapro “may prevent harmful changes in the heart that lead to heart failure.”

One of the telltale signs of heart failure 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.” The LogiRx tool evaluated 62 drugs that had been previously identified as promising candidates to prevent this. It was able to predict “’off-target’ effects for seven of these drugs that could help prevent harmful cellular hypertrophy, which were confirmed in cells for two of the drugs.” Then, the scientists evaluated those predictions by “doing lab tests and by looking at outcomes in patients taking the drugs. The latter revealed that patients taking [Lexapro] were significantly less likely to develop cardiac hypertrophy.”

While additional lab research and clinical trials are still needed to test the tool’s effectiveness, Jeffrey Saucerman, one of the researchers, is “excited about the potential of LogiRx for advancing and accelerating new treatments not just for cardiac hypertrophy but for a host of other serious medical conditions.”