Systems-Level Modeling of Epstein–Barr Virus and Multiple Sclerosis Pathogenesis

Principal investigator : Steven Sanche

Location : Université de Montréal

Financial support: 84,000CA$ over three years

Application deadline: January 20, 2026

We are seeking candidates with undergraduate and/or master’s degrees in a quantitative discipline such as mathematics, physics, bioinformatics, or related quantitative fields.

Summary

Join the Faculty of Pharmacy, a faculty at the forefront of multidisciplinary research, offering highly flexible training that is accessible to students from quantitative science backgrounds who wish to develop a strong understanding of biology and pharmaceutical sciences. The following project is suitable for candidates seeking to pursue a master’s degree or, ideally, a PhD at the Faculty of Pharmacy. Co-supervision with other investigators is possible.

Project overview

This project aims to develop a mathematical, systems-level modeling framework to investigate the role of Epstein–Barr virus (EBV) infection in the initiation and progression of multiple sclerosis (MS). Strong epidemiological evidence supports a causal link between EBV exposure and MS, yet the mechanistic pathways connecting viral persistence, immune dysregulation, and neuroinflammation remain incompletely understood. This project seeks to bridge this gap by constructing mechanistically grounded mathematical models that link biological processes across multiple scales.

Scientific objectives

The primary objective of the project is to formulate and analyze mechanistic models describing the dynamic interactions between EBV, immune cell populations (such as B cells, T cells and microglia), and inflammatory processes implicated in MS. These models will be designed to capture both within-host viral dynamics and system-level immune responses, while accounting for inter-individual variability and uncertainty.

Specific objectives include:

• Developing differential equation–based models to describe EBV latency, immune surveillance, and immune-mediated tissue damage.
• Integrating longitudinal clinical and biological data to inform and constrain model parameters.
• Investigating how variability in immune response or viral control may influence MS risk, disease progression, or relapse dynamics (analysis of trajectories).
• Using the models to explore hypothetical intervention scenarios, such as antiviral or immunomodulatory strategies, and to assess their potential impact on disease trajectories.

Methodological approach

The project will rely on mathematical modeling techniques commonly used in systems biology and pharmacology, including systems of ordinary and stochastic differential equations. Parameter estimation, uncertainty quantification, as well as dynamical and sensitivity analyses will be employed to link models to data and to identify key drivers of system behavior.

The modeling framework will emphasize biological interpretability and mechanistic consistency, ensuring that model components correspond to identifiable biological processes. Rather than focusing on prediction alone, the models will be used to generate testable hypotheses and to provide insight into the causal mechanisms underlying disease development.

Expected outcomes and impact

This project is expected to deliver:

• A mechanistic modeling framework for studying EBV–immune system interactions in the context of MS.
• Quantitative insights into the biological processes linking viral persistence and immune dysregulation to MS pathogenesis.
• A virtual experimentation platform to support hypothesis testing and exploration of therapeutic strategies.
• Generalizable modeling approaches applicable to other immune-mediated or infectious diseases.

By advancing mechanistic understanding of MS through quantitative modeling, this project will contribute to fundamental knowledge in neuroimmunology and support the rational design of future experimental and clinical studies.

How to apply: Please send a CV, a brief statement of interest, and transcripts to steven.sanche@umontreal.ca.

Link to principal investigator's webpage: https://pharm.umontreal.ca/faculte/lequipe/corps-professoral/fiche/in/in38502/sg/Steven%20Sanche/