The SATvac model of CD8+ T cell expansion and contraction phases considering memory and effector cell differentiation

Primary immune responses induce CD8+ T cell responses characterized by activation via antigen presenting cells, expansion, differentiation into effector and memory phenotypes, and contraction resulting in long-term memory populations. In this study a mathematical stochastic agent-based model is developed to simulate all phases of the CD8+ T cell response following vaccination. Importantly, the model successfully captures the stochastic nature of T cell dynamics throughout the response. It predicts T cell population with high accuracy while addressing mouse-to-mouse variability, highlighting its robust predictive power. This predictive model aims to improve T cell vaccination strategies by both informing the biology of the T cell response and streamlining vaccine development.Author summary: Vaccines work by stimulating immune cells to expand, and form populations that help protect the body. However, even when the same vaccine is given under controlled experimental conditions, the immune response can vary from one individual to another. In this study, we developed a computational model to study how this variability can arise during the response of CD8+ T cells vaccines. Our model represents individual cells and allows them to activate, divide, leave the modeled system, or become effector and memory cells. We used experimental data from vaccinated mice to estimate the model parameters and to compare the simulated immune response with measured cell counts over time. The model reproduced the main phases of the response, including expansion, peak response, and early contraction, while also generating variability between simulations. This work does not claim to capture every biological mechanism involved in immune response. Instead, it provides a framework for studying how stochastic single-cell events can influence population-level immune dynamics. Such models may help guide future studies that combine experimental data with simulation to better understand vaccine responses.