SynthesisFrontiers in immunology2024
Mathematical modeling in autoimmune diseases: from theory to clinical application.
Synthesis in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 5 citations in OpenAlex.
- Cell-based therapies of autoimmune diseases in the context of artificial intelligence development.Clinical and experimental medicine · 2026Review
- Engineering autoimmune disease models using organoids: Harnessing microenvironmental engineering for precision medicine and immunological recapitulation.Bioengineering & translational medicine · 2026Review
- Systematic Review and Model-Based Meta-Analysis of Targeted Drugs for Systemic Sclerosis.Pharmaceutics · 2026Review
- Quantitative systems pharmacology model of B cell immune response in mouse.Frontiers in immunology · 2026Article
- Machine Learning-Based Analysis of Serum Interleukin-39 and Interleukin-40 Levels for Differentiating Rheumatoid Arthritis and Systemic Lupus Erythematosus.Medeniyet medical journal · 2025Article
- Review
- An Integrative Mechanistic Model of Type 1 IFN-Mediated Inflammation in Systemic Lupus Erythematosus.CPT: pharmacometrics & systems pharmacology · 2025Article
- Conceptual quantitative systems pharmacology framework for supporting clinical trial design in organ-specific autoimmune and rare diseases.Frontiers in immunology · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The research & development (R&D) of novel therapeutic agents for the treatment of autoimmune diseases is challenged by highly complex pathogenesis and multiple etiologies of these conditions. The number of targeted therapies available on the market is limited, whereas the prevalence of autoimmune conditions in the global population continues to rise. Mathematical modeling of biological systems is an essential tool which may be applied in support of decision-making across R&D drug programs to improve the probability of success in the development of novel medicines. Over the past decades, multiple models of autoimmune diseases have been developed. Models differ in the spectra of quantitative data used in their development and mathematical methods, as well as in the level of "mechanistic granularity" chosen to describe the underlying biology. Yet, all models strive towards the same goal: to quantitatively describe various aspects of the immune response. The aim of this review was to conduct a systematic review and analysis of mathematical models of autoimmune diseases focused on the mechanistic description of the immune system, to consolidate existing quantitative knowledge on autoimmune processes, and to outline potential directions of interest for future model-based analyses. Following a systematic literature review, 38 models describing the onset, progression, and/or the effect of treatment in 13 systemic and organ-specific autoimmune conditions were identified, most models developed for inflammatory bowel disease, multiple sclerosis, and lupus (5 models each). ≥70% of the models were developed as nonlinear systems of ordinary differential equations, others - as partial differential equations, integro-differential equations, Boolean networks, or probabilistic models. Despite covering a relatively wide range of diseases, most models described the same components of the immune system, such as T-cell response, cytokine influence, or the involvement of macrophages in autoimmune processes. All models were thoroughly analyzed with an emphasis on assumptions, limitations, and their potential applications in the development of novel medicines.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.