Deriving mechanism-based pharmacodynamic models by reducing quantitative systems pharmacology models
- Quantitative systems pharmacology (QSP) models integrate comprehensive qualitative and quantitative knowledge about pharmacologically relevant processes. We previously proposed a first approach to leverage the knowledge in QSP models to derive simpler, mechanism-based pharmacodynamic (PD) models. Their complexity, however, is typically still too large to be used in the population analysis of clinical data. Here, we extend the approach beyond state reduction to also include the simplification of reaction rates, elimination of reactions, and analytic solutions. We additionally ensure that the reduced model maintains a prespecified approximation quality not only for a reference individual but also for a diverse virtual population. We illustrate the extended approach for the warfarin effect on blood coagulation. Using the model-reduction approach, we derive a novel small-scale warfarin/international normalized ratio model and demonstrate its suitability for biomarker identification. Due to the systematic nature of the approach inQuantitative systems pharmacology (QSP) models integrate comprehensive qualitative and quantitative knowledge about pharmacologically relevant processes. We previously proposed a first approach to leverage the knowledge in QSP models to derive simpler, mechanism-based pharmacodynamic (PD) models. Their complexity, however, is typically still too large to be used in the population analysis of clinical data. Here, we extend the approach beyond state reduction to also include the simplification of reaction rates, elimination of reactions, and analytic solutions. We additionally ensure that the reduced model maintains a prespecified approximation quality not only for a reference individual but also for a diverse virtual population. We illustrate the extended approach for the warfarin effect on blood coagulation. Using the model-reduction approach, we derive a novel small-scale warfarin/international normalized ratio model and demonstrate its suitability for biomarker identification. Due to the systematic nature of the approach in comparison with empirical model building, the proposed model-reduction algorithm provides an improved rationale to build PD models also from QSP models in other applications.…
Author details: | Undine FalkenhagenORCiD, Jane KnöchelORCiD, Charlotte Kloft, Wilhelm HuisingaORCiDGND |
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DOI: | https://doi.org/10.1002/psp4.12903 |
ISSN: | 2163-8306 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/36866520 |
Title of parent work (English): | CPT: Pharmacometrics & Systems Pharmacology |
Subtitle (English): | an application to warfarin |
Publisher: | Wiley |
Place of publishing: | Hoboken |
Publication type: | Article |
Language: | English |
Date of first publication: | 2023/03/03 |
Publication year: | 2023 |
Release date: | 2024/07/02 |
Volume: | 12 |
Issue: | 4 |
Number of pages: | 12 |
First page: | 432 |
Last Page: | 443 |
Funding institution: | Graduate Research Training Program PharMetrX: Pharmacometrics &; Computational Disease Modeling, Berlin/Potsdam, Germany |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
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 |