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The eight pillars of within-host tuberculosis modelling

  • University of Michigan

Research output: Contribution to journal › Review article › peer-review

Abstract

Tuberculosis (TB) remains a global health challenge, driven by multiscale pathogenesis across molecular, cellular, tissue, and systemic levels. Within-host mathematical modelling provides a powerful way to explore these processes, providing mechanistic insights that are difficult to capture experimentally, including host-pathogen interactions, immune regulation, and treatment efficacy. This review synthesises the evolution of TB models from early ordinary differential equation systems to agent-based and hybrid multiscale approaches, leading to integrated pharmacokinetic/pharmacodynamic and systems pharmacology frameworks. We highlight advances in omics-driven personalisation, virtual clinical trials for regimen optimisation, multiscale and multicompartment extensions, translational impact, evolutionary dynamics, and efforts to improve reproducibility. We also examine modelling strategies for TB coinfections and comorbidities, including HIV and diabetes, which reshape granuloma biology and drug exposure. Unlike previous reviews, we integrate historical and recent within-host tuberculosis modelling advances and present quantitative visual summaries in the form of theme-by-approach heatmaps. In this work, we identify emerging opportunities and current gaps in the landscape of TB models. In addition, we develop a unique workflow for this review that can be adapted for other modelling topics. Our synthesis provides a roadmap towards computational models that may support future precision therapy and TB control strategies.
Original languageEnglish
Article number1920524
Pages (from-to)1-22
Number of pages22
JournalFrontiers in Immunology
Volume17
Early online date3 Sept 2026
DOIs
Publication statusPublished - 3 Sept 2026

Funding

The author(s) declared that financial support was received for this work and/or its publication. RB acknowledges fellowship funding by UKRI Medical Research Council grant number MR/Y010124/1.

FundersFunder number
Medical Research CouncilMR/Y010124/1

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • granuloma
  • precision medicine
  • TB coinfection and comorbidity
  • tuberculosis
  • withinhost mathematical modelling
  • within-host mathematical modelling

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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