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What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk?
BACKGROUND: Biologically based dose–response (BBDR) models can incorporate data on biological processes at the cellular and molecular level to link external exposure to an adverse effect. OBJECTIVES: Our goal was to examine the utility of BBDR models in estimating low-dose risk. METHODS: We reviewed...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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National Institute of Environmental Health Sciences
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2866670/ https://www.ncbi.nlm.nih.gov/pubmed/20056564 http://dx.doi.org/10.1289/ehp.0901249 |
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author | Crump, Kenny S. Chen, Chao Chiu, Weihsueh A. Louis, Thomas A. Portier, Christopher J. Subramaniam, Ravi P. White, Paul D. |
author_facet | Crump, Kenny S. Chen, Chao Chiu, Weihsueh A. Louis, Thomas A. Portier, Christopher J. Subramaniam, Ravi P. White, Paul D. |
author_sort | Crump, Kenny S. |
collection | PubMed |
description | BACKGROUND: Biologically based dose–response (BBDR) models can incorporate data on biological processes at the cellular and molecular level to link external exposure to an adverse effect. OBJECTIVES: Our goal was to examine the utility of BBDR models in estimating low-dose risk. METHODS: We reviewed the utility of BBDR models in risk assessment. RESULTS: BBDR models have been used profitably to evaluate proposed mechanisms of toxicity and identify data gaps. However, these models have not improved the reliability of quantitative predictions of low-dose human risk. In this commentary we identify serious impediments to developing BBDR models for this purpose. BBDR models do not eliminate the need for empirical modeling of the relationship between dose and effect, but only move it from the whole organism to a lower level of biological organization. However, in doing this, BBDR models introduce significant new sources of uncertainty. Quantitative inferences are limited by inter- and intraindividual heterogeneity that cannot be eliminated with available or reasonably anticipated experimental techniques. BBDR modeling does not avoid uncertainties in the mechanisms of toxicity relevant to low-level human exposures. Although implementation of BBDR models for low-dose risk estimation have thus far been limited mainly to cancer modeled using a two-stage clonal expansion framework, these problems are expected to be present in all attempts at BBDR modeling. CONCLUSIONS: The problems discussed here appear so intractable that we conclude that BBDR models are unlikely to be fruitful in reducing uncertainty in quantitative estimates of human risk from low-level exposures in the foreseeable future. Use of in vitro data from recent advances in molecular toxicology in BBDR models is not likely to remove these problems and will introduce new issues regarding extrapolation of data from in vitro systems. |
format | Text |
id | pubmed-2866670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | National Institute of Environmental Health Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-28666702010-05-26 What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? Crump, Kenny S. Chen, Chao Chiu, Weihsueh A. Louis, Thomas A. Portier, Christopher J. Subramaniam, Ravi P. White, Paul D. Environ Health Perspect Commentary BACKGROUND: Biologically based dose–response (BBDR) models can incorporate data on biological processes at the cellular and molecular level to link external exposure to an adverse effect. OBJECTIVES: Our goal was to examine the utility of BBDR models in estimating low-dose risk. METHODS: We reviewed the utility of BBDR models in risk assessment. RESULTS: BBDR models have been used profitably to evaluate proposed mechanisms of toxicity and identify data gaps. However, these models have not improved the reliability of quantitative predictions of low-dose human risk. In this commentary we identify serious impediments to developing BBDR models for this purpose. BBDR models do not eliminate the need for empirical modeling of the relationship between dose and effect, but only move it from the whole organism to a lower level of biological organization. However, in doing this, BBDR models introduce significant new sources of uncertainty. Quantitative inferences are limited by inter- and intraindividual heterogeneity that cannot be eliminated with available or reasonably anticipated experimental techniques. BBDR modeling does not avoid uncertainties in the mechanisms of toxicity relevant to low-level human exposures. Although implementation of BBDR models for low-dose risk estimation have thus far been limited mainly to cancer modeled using a two-stage clonal expansion framework, these problems are expected to be present in all attempts at BBDR modeling. CONCLUSIONS: The problems discussed here appear so intractable that we conclude that BBDR models are unlikely to be fruitful in reducing uncertainty in quantitative estimates of human risk from low-level exposures in the foreseeable future. Use of in vitro data from recent advances in molecular toxicology in BBDR models is not likely to remove these problems and will introduce new issues regarding extrapolation of data from in vitro systems. National Institute of Environmental Health Sciences 2010-05 2010-01-04 /pmc/articles/PMC2866670/ /pubmed/20056564 http://dx.doi.org/10.1289/ehp.0901249 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Commentary Crump, Kenny S. Chen, Chao Chiu, Weihsueh A. Louis, Thomas A. Portier, Christopher J. Subramaniam, Ravi P. White, Paul D. What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title | What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title_full | What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title_fullStr | What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title_full_unstemmed | What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title_short | What Role for Biologically Based Dose–Response Models in Estimating Low-Dose Risk? |
title_sort | what role for biologically based dose–response models in estimating low-dose risk? |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2866670/ https://www.ncbi.nlm.nih.gov/pubmed/20056564 http://dx.doi.org/10.1289/ehp.0901249 |
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