ReviewFrontiers in immunology2025
Multi-physiology modeling of the immune system in the era of precision immunotherapy.
Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Decoding cellular population dynamics through mechanistic modelling and statistical data analysis.NPJ systems biology and applications · 2026Review
- Digital immune twins and ai-integrated multi-omic biomarkers: Redefining personalized immunotherapy in non-small cell lung cancer.Iranian journal of basic medical sciences · 2026Review
- Spatial topology and competitive access differentially shape early T cell priming in the lymph node: an agent-based modeling approach.Frontiers in immunology · 2026Article
- Amplification cycles through innate lymphoid cells at the onset of lupus nephritis.Frontiers in immunology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunotherapies using new modalities, including antibody-based drugs, nanoparticle-delivered drugs, and adoptive cell therapy, have become major treatment options for immune-related diseases such as cancer, autoimmune diseases, and infections. Although data characterizing individual patients' pharmacological responses, immune statuses, and clinical outcomes become increasingly available, predicting individual patients' immunotherapeutic responses for developing and deploying optimal immunotherapies remains challenging. Here, we propose "multi-physiology modeling" of the immune system that integrates omics-based and dynamic systems modeling-based systems immunology and pharmacometrics modeling on top of basic and clinical immunology. The multi-physiology modeling approach aims to integrate different physiological systems to realistically simulate the multi-scale and complex interactions of the immune system under intervention by immunotherapeutic agents for predictive immunotherapies tailored to individual patients. This will accelerate not only our understanding of basic immunology related to immune-related diseases but also the efficiency and accuracy of clinical immunotherapeutics in the era of precision immunotherapy.
Indexed as
Identifiers
What OpenQuestion holds
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.