Speaker
Description
Chimeric Antigen Receptor (CAR) T-cell therapy represents a frontier in treating leukemias and lymphomas, with recent clinical approvals worldwide. Despite its potential, therapeutic outcomes remain heterogeneous due to factors such as limited in vivo persistence, impaired migration, exhausted phenotypes, and tumor-mediated immunosuppression. Mathematical modeling offers a robust framework to predict these outcomes and elucidate biological mechanisms that are otherwise inaccessible through direct measurement. Our group has developed models incorporating diverse CAR T-cell phenotypes—including effector, exhausted, and memory cells—calibrated with data from public clinical trials. Furthermore, our models account for the roles of healthy B-cells and macrophages in clinical outcomes and the development of Cytokine Release Syndrome (CRS). Finally, we analyze antigen expression dynamics as a proxy for predicting antigen-positive and antigen-negative relapses. Overall, our multiscale models integrate in vitro and in vivo data to enhance the predictive understanding of CAR T-cell therapy in hematological malignancies.
