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PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions
As increasing amounts of biomonitoring survey data become available, a new discipline focused on converting such data into estimates of chemical exposures has developed. Reverse dosimetry uses a pharmacokinetic model along with measured biomarker concentrations to determine the plausible exposure co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3732445/ https://www.ncbi.nlm.nih.gov/pubmed/23930024 http://dx.doi.org/10.6026/97320630009707 |
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author | Grulke, Christopher M Holm, Kathleen Goldsmith, Michael-Rock Tan, Yu-Mei |
author_facet | Grulke, Christopher M Holm, Kathleen Goldsmith, Michael-Rock Tan, Yu-Mei |
author_sort | Grulke, Christopher M |
collection | PubMed |
description | As increasing amounts of biomonitoring survey data become available, a new discipline focused on converting such data into estimates of chemical exposures has developed. Reverse dosimetry uses a pharmacokinetic model along with measured biomarker concentrations to determine the plausible exposure concentrations-- a critical step to incorporate ground-truthing experimental data into a distribution of probable exposures that reduces model uncertainty and variability. At the population level, probabilistic reverse dosimetry can utilize a distribution of measured biomarker concentrations to identify the most likely exposure concentrations (or intake doses) experienced by the study participants. PROcEED is software that provides access to probabilistic reverse dosimetry approaches for estimating exposure distributions via a simple user interface. AVAILABILITY: PROcEED along with installation instructions is freely available for download from http://www.epa.gov/heasd/products/proceed/proceed.html |
format | Online Article Text |
id | pubmed-3732445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Biomedical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-37324452013-08-08 PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions Grulke, Christopher M Holm, Kathleen Goldsmith, Michael-Rock Tan, Yu-Mei Bioinformation Prediction Model As increasing amounts of biomonitoring survey data become available, a new discipline focused on converting such data into estimates of chemical exposures has developed. Reverse dosimetry uses a pharmacokinetic model along with measured biomarker concentrations to determine the plausible exposure concentrations-- a critical step to incorporate ground-truthing experimental data into a distribution of probable exposures that reduces model uncertainty and variability. At the population level, probabilistic reverse dosimetry can utilize a distribution of measured biomarker concentrations to identify the most likely exposure concentrations (or intake doses) experienced by the study participants. PROcEED is software that provides access to probabilistic reverse dosimetry approaches for estimating exposure distributions via a simple user interface. AVAILABILITY: PROcEED along with installation instructions is freely available for download from http://www.epa.gov/heasd/products/proceed/proceed.html Biomedical Informatics 2013-07-17 /pmc/articles/PMC3732445/ /pubmed/23930024 http://dx.doi.org/10.6026/97320630009707 Text en © 2013 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited. |
spellingShingle | Prediction Model Grulke, Christopher M Holm, Kathleen Goldsmith, Michael-Rock Tan, Yu-Mei PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title | PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title_full | PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title_fullStr | PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title_full_unstemmed | PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title_short | PROcEED: Probabilistic reverse dosimetry approaches for estimating exposure distributions |
title_sort | proceed: probabilistic reverse dosimetry approaches for estimating exposure distributions |
topic | Prediction Model |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3732445/ https://www.ncbi.nlm.nih.gov/pubmed/23930024 http://dx.doi.org/10.6026/97320630009707 |
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