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Challenge model of TNF(α) turnover at varying LPS and drug provocations
A mechanism-based biomarker model of TNF(α)-response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as k(t), k(out)), challenge characteristics (such as k(s), k(LPS), K(m, LPS), S(max), SC(50)) an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529397/ https://www.ncbi.nlm.nih.gov/pubmed/30778719 http://dx.doi.org/10.1007/s10928-019-09622-x |
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author | Held, Felix Hoppe, Edmund Cvijovic, Marija Jirstrand, Mats Gabrielsson, Johan |
author_facet | Held, Felix Hoppe, Edmund Cvijovic, Marija Jirstrand, Mats Gabrielsson, Johan |
author_sort | Held, Felix |
collection | PubMed |
description | A mechanism-based biomarker model of TNF(α)-response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as k(t), k(out)), challenge characteristics (such as k(s), k(LPS), K(m, LPS), S(max), SC(50)) and test-compound-related parameters (I(max), IC(50)). The exposure to test compound was modelled by means of first-order input and Michaelis–Menten type of nonlinear elimination. Test compound potency was estimated to 20 nM with a 70% partial reduction in TNF(α)-response at the highest dose of 30 mg·kg(−1). Future selection of drug candidates may focus the estimation on potency and efficacy by applying the selected structure consisting of TNF(α) system and LPS challenge characteristics. A related aim was to demonstrate how an exploratory (graphical) analysis may guide us to a tentative model structure, which enables us to better understand target biology. The analysis demonstrated how to tackle a biomarker with a baseline below the limit of detection. Repeated LPS-challenges may also reveal how the rate and extent of replenishment of TNF(α) pools occur. Lack of LPS exposure-time courses was solved by including a biophase model, with the underlying assumption that TNF(α)-response time courses, as such, contain kinetic information. A transduction type of model with non-linear stimulation of TNF(α) release was finally selected. Typical features of a challenge experiment were shown by means of model simulations. Experimental shortcomings of present and published designs are identified and discussed. The final model coupled to suggested guidance rules may serve as a general basis for the collection and analysis of pharmacological challenge data of future studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10928-019-09622-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6529397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-65293972019-06-07 Challenge model of TNF(α) turnover at varying LPS and drug provocations Held, Felix Hoppe, Edmund Cvijovic, Marija Jirstrand, Mats Gabrielsson, Johan J Pharmacokinet Pharmacodyn Original Paper A mechanism-based biomarker model of TNF(α)-response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as k(t), k(out)), challenge characteristics (such as k(s), k(LPS), K(m, LPS), S(max), SC(50)) and test-compound-related parameters (I(max), IC(50)). The exposure to test compound was modelled by means of first-order input and Michaelis–Menten type of nonlinear elimination. Test compound potency was estimated to 20 nM with a 70% partial reduction in TNF(α)-response at the highest dose of 30 mg·kg(−1). Future selection of drug candidates may focus the estimation on potency and efficacy by applying the selected structure consisting of TNF(α) system and LPS challenge characteristics. A related aim was to demonstrate how an exploratory (graphical) analysis may guide us to a tentative model structure, which enables us to better understand target biology. The analysis demonstrated how to tackle a biomarker with a baseline below the limit of detection. Repeated LPS-challenges may also reveal how the rate and extent of replenishment of TNF(α) pools occur. Lack of LPS exposure-time courses was solved by including a biophase model, with the underlying assumption that TNF(α)-response time courses, as such, contain kinetic information. A transduction type of model with non-linear stimulation of TNF(α) release was finally selected. Typical features of a challenge experiment were shown by means of model simulations. Experimental shortcomings of present and published designs are identified and discussed. The final model coupled to suggested guidance rules may serve as a general basis for the collection and analysis of pharmacological challenge data of future studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10928-019-09622-x) contains supplementary material, which is available to authorized users. Springer US 2019-02-18 2019 /pmc/articles/PMC6529397/ /pubmed/30778719 http://dx.doi.org/10.1007/s10928-019-09622-x Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Held, Felix Hoppe, Edmund Cvijovic, Marija Jirstrand, Mats Gabrielsson, Johan Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title | Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title_full | Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title_fullStr | Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title_full_unstemmed | Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title_short | Challenge model of TNF(α) turnover at varying LPS and drug provocations |
title_sort | challenge model of tnf(α) turnover at varying lps and drug provocations |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529397/ https://www.ncbi.nlm.nih.gov/pubmed/30778719 http://dx.doi.org/10.1007/s10928-019-09622-x |
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