Cell-level systems biology model to study inflammatory bowel diseases and their treatment options
- To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy.To help understand the complex and therapeutically challenging inflammatory bowel diseases (IBDs), we developed a systems biology model of the intestinal immune system that is able to describe main aspects of IBD and different treatment modalities thereof. The model, including key cell types and processes of the mucosal immune response, compiles a large amount of isolated experimental findings from literature into a larger context and allows for simulations of different inflammation scenarios based on the underlying data and assumptions. In the context of a large and diverse virtual IBD population, we characterized the patients based on their phenotype (in contrast to healthy individuals, they developed persistent inflammation after a trigger event) rather than on a priori assumptions on parameter differences to a healthy individual. This allowed to reproduce the enormous diversity of predispositions known to lead to IBD. Analyzing different treatment effects, the model provides insight into characteristics of individual drug therapy. We illustrate for anti-TNF-alpha therapy, how the model can be used (i) to decide for alternative treatments with best prospects in the case of nonresponse, and (ii) to identify promising combination therapies with other available treatment options.…
Author details: | Sabine StüblerORCiDGND, Charlotte KloftORCiDGND, Wilhelm HuisingaORCiDGND |
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DOI: | https://doi.org/10.1002/psp4.12932 |
ISSN: | 2163-8306 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/36727252 |
Title of parent work (English): | CPT: pharmacometrics & systems pharmacology |
Publisher: | Nature Publ. Group |
Place of publishing: | London |
Publication type: | Article |
Language: | English |
Date of first publication: | 2023/05/18 |
Publication year: | 2023 |
Release date: | 2024/07/02 |
Volume: | 12 |
Issue: | 5 |
Number of pages: | 16 |
First page: | 690 |
Last Page: | 705 |
Funding institution: | Graduate Research Training Program PharMetrX: Pharmacometrics &; Computational Disease Modeling, Berlin/Potsdam, Germany |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie | |
DDC classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Peer review: | Referiert |
Grantor: | Publikationsfonds der Universität Potsdam |
Publishing method: | Open Access / Gold Open-Access |
DOAJ gelistet | |
License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |