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Screening Assays to Characterize Novel Endothelial Regulators Involved in the Inflammatory Response
Published on: September 15, 2017
Pharmacokinetic/pharmacodynamic modeling in inflammation
Hoi-Kei Lon1, Dongyang Liu, William J Jusko
1Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY 14214, USA.
This review explores mathematical models for inflammation, detailing how pharmacokinetic/pharmacodynamic (PK/PD) models capture drug effects and disease progression. Advanced models offer better insights into inflammation treatment and drug development.
Area of Science:
- Pharmacology
- Immunology
- Mathematical Biology
Background:
- Inflammation is a complex immune response underlying chronic diseases like arthritis, diabetes, and cancer.
- Mathematical modeling is crucial for understanding disease progression and evaluating anti-inflammatory drugs.
Purpose of the Study:
- To review the state-of-the-art in modeling anti-inflammatory drug effects.
- To describe relevant biomarkers for modeling and summarize PK/PD model limitations.
- To highlight advancements in mechanistic modeling for inflammation.
Main Methods:
- Review of published pharmacokinetic/pharmacodynamic (PK/PD) models for anti-inflammatory drugs.
- Analysis of direct inhibitory, indirect response, target-mediated, and transduction models.
- Discussion of systems modeling for biologics and mechanistic models.
Main Results:
- Simple models describe in vitro drug effects; indirect response models capture symptom/biomarker turnover.
- PK/PD models successfully describe anti-inflammatory drug action and inflammation progression.
- Biologics and advanced mechanistic models enable quantitative capture of physiological processes.
Conclusions:
- Diverse modeling approaches, from simple to complex mechanistic systems, are vital for understanding inflammation.
- Advanced models can evaluate key mediators, drug interactions, and improve in vitro-to-in vivo translation.
- Modeling offers powerful tools for developing novel anti-inflammatory therapies.
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