Multiple Sclerosis disease: a computational approach for investigating its drug interactions

TL;DR

This paper introduces a computational model to study Multiple Sclerosis progression and drug interactions, specifically analyzing the effects of Daclizumab, leveraging system symmetries to simplify complex analysis.

Contribution

The paper presents a novel in silico model for MS evolution and drug effects, incorporating spatial and temporal factors and exploiting symmetries for analysis simplification.

Findings

Model effectively simulates MS progression and drug impact.

Symmetry exploitation reduces computational complexity.

Provides a new tool for in silico MS research.

Abstract

Multiple Sclerosis (MS) is a chronic and potentially highly disabling disease that can cause permanent damage and deterioration of the central nervous system. In Europe it is the leading cause of non-traumatic disabilities in young adults, since more than 700,000 EU people suffer from MS. Although recent studies on MS pathophysiology have been provided, MS remains a challenging disease. In this context, thanks to recent advances in software and hardware technologies, computational models and computer simulations are becoming appealing research tools to support scientists in the study of such disease. Thus, motivated by this consideration we propose in this paper a new model to study the evolution of MS in silico, and the effects of the administration of Daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the system can be exploited to drastically reduce the complexity of its analysis.