Evidence map›Paper›PMID 42148090›Full record

ArticleFrontiers in immunology2026

Quantitative systems pharmacology model of B cell immune response in mouse.

Yaroslav Ugolkov, Alina Volkova, Gabriel Helmlinger, Kirill Peskov, Victor Sokolov

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yaroslav UgolkovFaculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia.
Alina VolkovaMarchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS), Moscow, Russia.
Gabriel HelmlingerQuantitative Medicines, Lexington, MA, United States.
Kirill PeskovMarchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS), Moscow, Russia.
Victor SokolovMarchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS), Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

B cell-mediated immunity plays a crucial role in long-term humoral protection. However, dysregulation of B cell development and differentiation may lead to the persistence of autoreactive clones, contributing to autoimmune diseases. Despite a number of therapeutic agents in preclinical and clinical development targeting B cell biology, several challenges still limit their successful translation into clinical use. To better understand B cell-targeting mechanisms of action quantitatively and mechanistically, we developed an integrative systems pharmacology model that describes T cell-dependent B cell response to antigen exposure in mouse. The model includes 20 ordinary differential equations representing key biological processes involved in the B lymphocyte response: B cell activation in secondary lymphoid organs; antibody-secreting cell (ASC) generation; migration to the bone marrow; and redistribution to peripheral tissues. The model adequately described ASC dynamics across tissues and IgG time profiles in plasma. Local and global sensitivity analyses identified the ASC production rate as the main contributor to cell counts in the spleen and in lymph nodes, while ASC levels in the bone marrow were primarily controlled by their influx rate, reflecting survival niche availability. Moderate variations of this influx rate parameter allowed the model to capture high inter-study variability in bone marrow ASC levels, explaining the observed heterogeneity in the functional immune response. The model can be further used as a quantitative tool to study B cell responses and their dysregulation in autoimmunity. It can be extended by integrating plasma-cell biology and autoantibody production, ultimately supporting the development of new therapeutic strategies for autoimmune diseases.

Indexed as

B-LymphocytesModels, ImmunologicalAnimalsAntibody-Producing CellsImmunoglobulin GLymphocyte ActivationMiceSystems BiologyT-LymphocytesImmunoglobulin Gantibody secreting cell (ASC)B cell immunityMIDD (model-informed drug development)pharmacometric modelingQSP modelquantitative systems pharmacologysystemic autoimmune diseases

Identifiers

PMID42148090
PMCPMC13171755

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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.