Presentation description

This project utilizes agent-based modeling (ABM) to simulate and analyze T cell infiltration dynamics within heterogeneous tumors. T cell infiltration is a critical aspect of the immune response against cancer, influenced by various factors including tumor architecture, spatial distribution of tumor cells, and local immune checkpoints. Traditional mathematical models often oversimplify these complexities, whereas ABM offers a more granular approach by simulating individual T cells and tumor cells as autonomous agents with defined behaviors and interactions.

The ABM framework developed here incorporates spatial and temporal dynamics to explore how T cells navigate through and interact with different tumor regions. The model accounts for realistic tumor heterogeneity by incorporating varying densities and distributions of cancer cells, which influence T cell infiltration patterns. Moreover, the simulation integrates signaling pathways and immune checkpoint interactions that regulate T cell activation and exhaustion within the tumor.

Overall, this ABM approach serves as a valuable tool for studying complex interactions within the tumor, offering insights that could inform therapeutic strategies aimed at promoting effective T cell infiltration and improving immunotherapy outcomes in heterogeneous tumors. Future directions include refining the model with experimental data validation and exploring personalized treatment strategies tailored to individual tumor spatial profiles.