Across USC’s schools and campuses, researchers, faculty and practitioners are developing innovative solutions for societal issues, imagining new approaches to making art and finding ways for creators to prepare for a shifting landscape as AI increasingly intersects with different fields.

Under USC President Beong-Soo Kim’s leadership, advancing ethical AI that puts people first has become a university priority — building on USC’s legacy of innovation while preparing the next generation of researchers, scientists, engineers, entrepreneurs, artists and health professionals. 

This story is part of Trojan Family Magazine’s AI series highlighting the people and ideas driving USC’s vision forward. 

AI is helping USC researchers answer a question with life-or-death consequences: Why do medications work well for some patients but not others?

Gauri Rao, associate professor of clinical pharmacy at the USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, is the director of the Center for Quantitative Drug and Disease Modeling. At her lab, Rao and her team are using machine learning to find the answer, analyzing vast amounts of bacterial genomic and metabolomic data to better understand the mechanisms that drive antimicrobial resistance.

By identifying patterns in bacterial genomes and metabolic pathways, the team aims to predict how bacteria develop resistance to antibiotics and uncover strategies to preserve the effectiveness of existing therapies. Their work combines advanced computational approaches with experimental research to address one of the world’s most pressing public health challenges.

“Developing a new antibiotic is incredibly costly and can take more than a decade,” Rao says. “Given the urgent rise in antimicrobial resistance, we are focused on using machine learning and quantitative modeling to maximize the effectiveness of the antibiotics we already have and help slow the emergence of resistance.”

Given the growing threat of drug-resistant infections, a large portion of Rao’s research program is dedicated to bacteriophage (phage) therapy, an emerging approach that uses naturally occurring viruses to target and kill bacteria. Rao says machine learning is critical for helping researchers rapidly identify phages that are most likely to be effective against specific bacterial pathogens.

Rao is part of the National Institutes of Health’s first coordinated U.S. research network for phage therapeutics. Through this collaborative effort, computational approaches, including machine learning, are integrated with laboratory (in vitro) and animal model (in vivo) testing to identify promising phage candidates and accelerate their translation into clinical practice. The goal is to develop more precise and effective treatments for multidrug-resistant infections while preserving the effectiveness of current antibiotics.

Prashant Dogra, associate director of the center and assistant professor of clinical pharmacy at USC Mann, also integrates mechanistic mathematical modeling with AI to better understand disease mechanisms and drug delivery systems.

One of Dogra’s current projects, supported by funding from the NIH, studies how nanomedicines move through the body to design safer and more effective drug delivery systems to transform treatment for diseases ranging from cancer to chronic illnesses.

Using machine learning, he analyzes a large body of published studies to identify design principles for safer and more effective nanoparticles, potentially leading to better clinical outcomes for patients.

Dogra, who joined the USC Mann faculty last year, says he can’t imagine doing the projects he’s currently working on at any other university.

“I think USC has a very interdisciplinary environment that I find is really unmatchable,” Dogra says. “Having access to colleagues who are very strong in complementary domains facilitates newer ways of thinking and allows us to develop these novel methods of pursuing our scientific questions.”

Read the entire series: USC at the Leading Edge of AI

Part 1: The Business Students | Part 2: The Pharmaceutical Developers | Part 3: The Creatives | Part 4: The Filmmaker | Part 5: The Urban Planners