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Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models
Exposure–response modeling facilitates effective dosing regimen selection in clinical drug development, where the end points are often disease scores and not physiological variables. Appropriate models need to be consistent with pharmacology and identifiable from the time courses of available data....
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4076802/ https://www.ncbi.nlm.nih.gov/pubmed/24897307 http://dx.doi.org/10.1038/psp.2014.15 |
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author | Hu, C |
author_facet | Hu, C |
author_sort | Hu, C |
collection | PubMed |
description | Exposure–response modeling facilitates effective dosing regimen selection in clinical drug development, where the end points are often disease scores and not physiological variables. Appropriate models need to be consistent with pharmacology and identifiable from the time courses of available data. This article describes a general framework of applying mechanism-based models to various types of clinical end points. Placebo and drug model parameterization, interpretation, and assessment are discussed with a focus on the indirect response models. |
format | Online Article Text |
id | pubmed-4076802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-40768022014-07-01 Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models Hu, C CPT Pharmacometrics Syst Pharmacol Tutorial Exposure–response modeling facilitates effective dosing regimen selection in clinical drug development, where the end points are often disease scores and not physiological variables. Appropriate models need to be consistent with pharmacology and identifiable from the time courses of available data. This article describes a general framework of applying mechanism-based models to various types of clinical end points. Placebo and drug model parameterization, interpretation, and assessment are discussed with a focus on the indirect response models. Nature Publishing Group 2014-06 2014-06-04 /pmc/articles/PMC4076802/ /pubmed/24897307 http://dx.doi.org/10.1038/psp.2014.15 Text en Copyright © 2014 American Society for Clinical Pharmacology and Therapeutics http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Tutorial Hu, C Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title | Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title_full | Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title_fullStr | Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title_full_unstemmed | Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title_short | Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models |
title_sort | exposure–response modeling of clinical end points using latent variable indirect response models |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4076802/ https://www.ncbi.nlm.nih.gov/pubmed/24897307 http://dx.doi.org/10.1038/psp.2014.15 |
work_keys_str_mv | AT huc exposureresponsemodelingofclinicalendpointsusinglatentvariableindirectresponsemodels |