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Quantitative systems toxicology
The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of eva...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5754001/ https://www.ncbi.nlm.nih.gov/pubmed/29308440 http://dx.doi.org/10.1016/j.cotox.2017.07.003 |
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author | Bloomingdale, Peter Housand, Conrad Apgar, Joshua F. Millard, Bjorn L. Mager, Donald E. Burke, John M. Shah, Dhaval K. |
author_facet | Bloomingdale, Peter Housand, Conrad Apgar, Joshua F. Millard, Bjorn L. Mager, Donald E. Burke, John M. Shah, Dhaval K. |
author_sort | Bloomingdale, Peter |
collection | PubMed |
description | The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of evaluating the adverse effects of drugs in animals to predict human health risks. The U.S. Environmental Protection Agency recognized the need to develop innovative toxicity testing strategies and asked the National Research Council to develop a long-range vision and strategy for toxicity testing in the 21st century. The vision aims to reduce the use of animals and drug development costs through the integration of computational modeling and in vitro experimental methods that evaluates the perturbation of toxicity-related pathways. Towards this vision, collaborative quantitative systems pharmacology and toxicology modeling endeavors (QSP/QST) have been initiated amongst numerous organizations worldwide. In this article, we discuss how quantitative structure-activity relationship (QSAR), network-based, and pharmacokinetic/pharmacodynamic modeling approaches can be integrated into the framework of QST models. Additionally, we review the application of QST models to predict cardiotoxicity and hepatotoxicity of drugs throughout their development. Cell and organ specific QST models are likely to become an essential component of modern toxicity testing, and provides a solid foundation towards determining individualized therapeutic windows to improve patient safety. |
format | Online Article Text |
id | pubmed-5754001 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-57540012018-01-04 Quantitative systems toxicology Bloomingdale, Peter Housand, Conrad Apgar, Joshua F. Millard, Bjorn L. Mager, Donald E. Burke, John M. Shah, Dhaval K. Curr Opin Toxicol Article The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of evaluating the adverse effects of drugs in animals to predict human health risks. The U.S. Environmental Protection Agency recognized the need to develop innovative toxicity testing strategies and asked the National Research Council to develop a long-range vision and strategy for toxicity testing in the 21st century. The vision aims to reduce the use of animals and drug development costs through the integration of computational modeling and in vitro experimental methods that evaluates the perturbation of toxicity-related pathways. Towards this vision, collaborative quantitative systems pharmacology and toxicology modeling endeavors (QSP/QST) have been initiated amongst numerous organizations worldwide. In this article, we discuss how quantitative structure-activity relationship (QSAR), network-based, and pharmacokinetic/pharmacodynamic modeling approaches can be integrated into the framework of QST models. Additionally, we review the application of QST models to predict cardiotoxicity and hepatotoxicity of drugs throughout their development. Cell and organ specific QST models are likely to become an essential component of modern toxicity testing, and provides a solid foundation towards determining individualized therapeutic windows to improve patient safety. 2017-08-02 2017-06 /pmc/articles/PMC5754001/ /pubmed/29308440 http://dx.doi.org/10.1016/j.cotox.2017.07.003 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Bloomingdale, Peter Housand, Conrad Apgar, Joshua F. Millard, Bjorn L. Mager, Donald E. Burke, John M. Shah, Dhaval K. Quantitative systems toxicology |
title | Quantitative systems toxicology |
title_full | Quantitative systems toxicology |
title_fullStr | Quantitative systems toxicology |
title_full_unstemmed | Quantitative systems toxicology |
title_short | Quantitative systems toxicology |
title_sort | quantitative systems toxicology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5754001/ https://www.ncbi.nlm.nih.gov/pubmed/29308440 http://dx.doi.org/10.1016/j.cotox.2017.07.003 |
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