Howard University researchers advance cancer detection with AI imaging and protein targeting

Researchers at Howard University are working to improve cancer detection, treatment, and understanding through projects in imaging, chemistry, and artificial intelligence. Kofi Deh, Jacqueline Smith, and Anietie Andy lead the research with support from grants and a multi-institutional U54 pilot through a Howard University and Johns Hopkins University partnership. The work involves the College of Engineering and Architecture and the College of Arts and Sciences. Scholars participated last month in an American Cancer Society funding opportunities information session as part of Research Month programming. Carla Williams, interim director of the Howard University Cancer Center, said that when faculty secure funding they create paid research positions and hands-on opportunities for students. Kofi Deh, an assistant professor in the Department of Physics and Astronomy, develops advanced MRI methods including Chemical Exchange Saturation Transfer imaging to probe tumor biology. Deh also focuses on federated learning that allows hospitals to improve AI models collaboratively without sharing sensitive patient data. His goal is to translate lab innovations for broader access to advanced imaging and cancer care at Howard and beyond. Jacqueline Smith, an associate professor of chemistry, develops small molecules to target cancer cells with greater specificity than conventional treatments. Her research targets proteins linked to metastasis and explores drug delivery systems using proteins on cancer cell surfaces. Through a Howard-Hopkins Cancer Center pilot award she examines how molecular targets differ among patient groups and how they intersect with neighborhood conditions. Anietie Andy, an assistant professor in the College of Engineering and Architecture, directs the Howard University Natural Language Processing Group. He develops AI models combining medical data, imaging, lab results, and clinical notes to predict cancer risk in breast and colon cancer. His work is being developed into a National Institutes of Health R01 proposal as part of the Howard University AI in Healthcare Center.