A five-year, $2.2 million R01 grant from the National Institutes of Health (NIH) to Rutgers University‒Camden is supporting research to help drug manufacturers produce medications that won’t cause liver damage to patients.

“Liver toxicity is a leading safety concern in the development of new chemicals, such as new drugs,” says Hao Zhu, a Rutgers‒Camden chemistry professor who is the principal investigator on this research program.

Titled “Mechanism-Driven Virtual Adverse Outcome Pathway Modeling for Hepatotoxicity,” Zhu’s research project at Rutgers University–Camden has received a prestigious and highly competitive R01 grant from the NIH. The award is considered among the most respected mechanisms of financial support for medical research. The Rutgers–Camden scholar’s grant is awarded through the National Institute of Environmental Health Sciences.

“This is a significant accomplishment for Dr. Zhu and is a testament to the innovative and potentially lifesaving research that’s being conducted at Rutgers–Camden,” says Rutgers University–Camden Provost Michael Palis.

Zhu and his co-investigators – Sunil Shende, a Rutgers‒Camden professor of computer science, and Lauren Aleksunes and Wen Xia of Rutgers–New Brunswick – are working to develop a publicly accessible, web-based predictive model to evaluate new chemicals for risk of liver toxicity. The prediction result could be used to avoid toxic compounds in the development process and directly impact drug discovery, toxicology, and public health.

Current computational models are not applicable to predict whether a chemical is toxic or nontoxic to the liver. Zhu’s innovative computational model can emphasize why a chemical can cause liver damage.

“Every liver toxicant identified by the model will have a virtually developed toxicity pathway to show how it realizes its liver toxicity in the human body,” explains Zhu.

“It’s an honor to receive the grant because it is difficult to get, especially for small schools,” continues the Rutgers–Camden researcher, who is working from his home in Chapel Hill, N.C. during the coronavirus pandemic.

Using new AI algorithms and public big data sources, the research team, which includes three graduate students and one undergraduate, will construct computational models that will directly evaluate the liver toxicity potentials of chemicals.