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Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance
Quantitative Systems Pharmacology (QSP) models provide a means of integrating knowledge into a quantitative framework and, ideally, this integration leads to a better understanding of biology and better predictions of new experiments and clinical trials. In practice, these goals may be compromised b...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6118293/ https://www.ncbi.nlm.nih.gov/pubmed/29761883 http://dx.doi.org/10.1002/psp4.12311 |
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author | Stein, Andrew M. Looby, Michael |
author_facet | Stein, Andrew M. Looby, Michael |
author_sort | Stein, Andrew M. |
collection | PubMed |
description | Quantitative Systems Pharmacology (QSP) models provide a means of integrating knowledge into a quantitative framework and, ideally, this integration leads to a better understanding of biology and better predictions of new experiments and clinical trials. In practice, these goals may be compromised by model complexity and uncertainty. To address these problems, we recommend that the predictive performance of QSP models be assessed through comparison with simpler models developed specifically for this purpose. |
format | Online Article Text |
id | pubmed-6118293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61182932018-09-04 Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance Stein, Andrew M. Looby, Michael CPT Pharmacometrics Syst Pharmacol Perspectives Quantitative Systems Pharmacology (QSP) models provide a means of integrating knowledge into a quantitative framework and, ideally, this integration leads to a better understanding of biology and better predictions of new experiments and clinical trials. In practice, these goals may be compromised by model complexity and uncertainty. To address these problems, we recommend that the predictive performance of QSP models be assessed through comparison with simpler models developed specifically for this purpose. John Wiley and Sons Inc. 2018-08-22 2018-08 /pmc/articles/PMC6118293/ /pubmed/29761883 http://dx.doi.org/10.1002/psp4.12311 Text en © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Perspectives Stein, Andrew M. Looby, Michael Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title | Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title_full | Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title_fullStr | Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title_full_unstemmed | Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title_short | Benchmarking QSP Models Against Simple Models: A Path to Improved Comprehension and Predictive Performance |
title_sort | benchmarking qsp models against simple models: a path to improved comprehension and predictive performance |
topic | Perspectives |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6118293/ https://www.ncbi.nlm.nih.gov/pubmed/29761883 http://dx.doi.org/10.1002/psp4.12311 |
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