Poster L15 - A Mathematical Model for Naïve T cell Migration Kinetics

Introduction: Vaccines that induce a memory T cell response are promising candidates as immunization strategies for infections that are not prevented by antibodies alone, such as viral variants as we have seen most recently with COVID-19. T cell vaccines could also be used for cancer treatment since memory T cells can prevent relapse. However, developing T cell-inducing vaccines is hindered by the time and resources required to move vaccines into the clinic. One way to overcome this challenge is to create a mathematical model that can simulate T cell responses to different vaccine strategies. This will allow rapid testing of vaccine formulations, dosing, and administration sites. In addition, it can provide more insight into the T cell response throughout the body from blood sampling alone.

Materials and

Methods: In this work, we created a stochastic, First-Principles model that can predict T cell counts in different tissues of the body over time. The significance of the stochastic element is to provide knowledge on patient-to-patient variations. The unique structure of our model gives it an advantage over others in the literature as it connects the different body tissues which can explain the kinetics of T cell exchange between the blood and these tissues, and accurately estimate the parameters that govern cell re-circulation patterns. This work focuses on the re-circulation of naïve T cells before their interaction with antigen presenting cells (APCs). The model predicts cell counts in lymph nodes that drain different sites in the body (Skin LNs, Mesenteric LNs, and Draining LNs), the spleen (including the red pulp and white pulp), and the blood system.

Results, Conclusions, and Discussions: The attached figure shows a sample of the results of 100 runs of the model; the purple shaded area represents the cell counts at the different tissues for 15 hours post injections, while the black line represents the average of all the runs. The triangles represent the average experimental data points sampled from 4-5 mice per time point. The model fits the data points for almost all the time points and the parameter estimates align with ranges found in the literature. The model showed that the average residence time for a cell in any of the lymph node types varied between 5.5 – 8 hours. In future work, the model will be expanded to include the activation phase of T cells and will track the cell counts of each cell generation produced in each tissue over time.

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