The University of Maryland is backing a new effort to use quantum computing and artificial intelligence to speed the search for better ways to detect and treat cancer.
The project is one of 11 research efforts funded through the university’s Grand Challenges Grants Program, a three-year initiative that will provide nearly $15 million for work aimed at major social, health and technology problems, according to a university press release. The cancer project is supported as a team grant and brings together researchers from the A. James Clark School of Engineering and the College of Computer, Mathematical, and Natural Sciences.
The research will focus on single-atom catalysts, a class of materials made by placing isolated metal atoms on a supporting surface, according to the university. These materials can drive chemical reactions with high precision and have drawn interest as possible tools in cancer treatment and detection. In cancer therapy, they may help alter the tumor microenvironment, the local area around cancer cells that can influence how tumors grow, resist treatment and respond to therapy.
The University of Maryland team — which includes which includes Teng Li, Keystone Professor, Department of Mechanical Engineering, Maryland Energy Innovation Institute; Lianping Wu, assistant research professor of mechanical engineering and Xiaodi Wu, associate professor of computer science — plans to combine quantum computing and machine learning to design these catalysts more quickly and more accurately than conventional methods allow, according to the project summary. The goal is to build a predictive framework that can identify promising materials for cancer detection and therapy before they move into laboratory testing.