School of Medicine scientists at the University of Virginia (UVA), US have developed an AI tool, LogiRx, designed to expedite the development of treatments for new diseases by predicting the effects of drugs on biological processes.
The computational tool helps identify not only the patient populations that may benefit but also provides insights into how drugs function within cells.
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According to the researchers, LogiRx has shown potential in detecting a “promising” candidate for heart failure prevention.
For instance, the team found that escitalopram, an antidepressant, is a candidate to avert cardiac hypertrophy, a condition where the overgrown cells “thicken” the muscles of the heart, impairing the organ’s ability to pump blood.
UVA biomedical engineering professor Jeffrey Saucerman and his team, including PhD student Taylor Eggertsen, utilised LogiRx to assess 62 drugs previously deemed “promising” for preventing cardiac hypertrophy.
The tool predicted “off-target” effects for seven drugs that could aid in cellular hypertrophy prevention, with confirmation in cells for two of them.
Laboratory tests and patient outcome reviews revealed that those taking the antidepressant had a reduced risk of developing cardiac hypertrophy.
While further research and clinical trials are necessary before escitalopram can be prescribed for heart health, Saucerman is optimistic about the tool’s potential to expedite new treatments for various severe medical conditions.
Saucerman said: “AI needs to move from detecting patterns to generating understanding. Our LogiRx tool helps us identify not just which drugs can be repurposed for heart disease but how they work in the heart.
“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. LogiRx is a step towards combining AI with existing knowledge of how cells work to find new uses for old drugs.”
