An exciting collaboration between the Ragon Institute and the Jameel Clinic at MIT has achieved a significant milestone in leveraging artificial intelligence (AI) to aid the development of T cell vaccine candidates.
Ragon faculty member Gaurav Gaiha, MD, DPhil, and MIT Professor Regina Barzilay, PhD, AI lead of the Jameel Clinic for AI and Health, have published research in Nature Machine Intelligence introducing MUNIS-a deep learning tool designed to predict CD8+ T cell epitopes with unprecedented accuracy. This advancement has the potential to accelerate vaccine development against various infectious diseases.
The project marks a major first outcome from the Mark and Lisa Schwartz AI/ML Initiative at the Ragon Institute, which aims to integrate artificial intelligence, machine learning, and translational immunology to prevent and cure infectious diseases of global importance. This initiative was made possible through the generous support of Ragon Institute Board Chair Mark Schwartz and his wife, Lisa Schwartz.
By combining the Gaiha Lab’s expertise in T cell immunology with the Barzilay Lab’s pioneering work in AI, the team-led by co-first authors Jeremy Wohlwend, PhD, and Anusha Nathan, PhD-sought to address a longstanding challenge in vaccine development: the rapid and accurate identification of T cell epitopes in foreign pathogens. Epitopes are specific regions of an antigen that are recognized by the body’s immune cells and are critical for activating targeted immune responses.
Traditional methods for predicting epitopes often fall short in speed and accuracy. By integrating machine learning, researchers can now achieve faster and more efficient identification of