Fingolimod and Neuroinflammation in MS: Representing CD8+ T-Cell Dynamics Through Mathematical Modeling and Clinical Evidence

Background: Multiple sclerosis (MS), a debilitating chronic disease of the central nervous system, is characterized by both inflammatory and neurodegenerative processes that lead to demyelination and neuronal damage. While MS remains incurable, therapies like fingolimod can slow disease progression by modulating immune function. Fingolimod acts as a sphingosine-1-phosphate receptor modulator, limiting lymphocyte migration into the central nervous system and thereby reducing inflammation. Methods: In this study, we developed a computational model to describe fingolimod’s impact on immune dynamics in MS, focusing on CD8+ T-cell migration blockade. Model calibration utilized cohort data, enabling the comparison of simulated outcomes with observed clinical metrics. Results: The results indicate that our model effectively captures the timing and extent of CD8+ T-cell sequestration, consistent with key features in the patient data. Conclusions: These findings suggest that computational modeling can provide quantitative insight into the fingolimod’s mechanism of action and assist in predicting treatment response, offering a promising framework for exploring personalized fingolimod dosing strategies and enhancing therapeutic planning in MS.