Awarded in 2018
Home Department: Genetics, Medicine
Faculty Advisors: Ash Alizadeh (Medicine—Oncology) and Russ Altman (Bioengineering, Genetics, Medicine—BMIR, and Biomedical Data Science)
Research Title: Deep learning for personalized cancer vaccine design
Research Description: Personalized cancer vaccines provide a promising approach to prolonging patient survival. However, current cancer vaccine design strategies have limited accuracy, as they ignore many features that may play a role in patient immune response. Binbin will develop T-REx (T-cell Response Estimator), a more reliable deep learning model, to predict T-cell responses to a foreign peptide/neoantigen, which will then be applied to 3 cancer vaccine trials with 330+ patients along with other relevant models to determine important predictors for patient responses. By combining the fields of cancer immunology, machine learning, and clinical oncology, Binbin will provide a reliable computational algorithm to predict peptide immunogenicity as well as patient response predictors that will guide the design of future cancer vaccines.