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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...

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Detalles Bibliográficos
Autores principales: Grulke, Christopher M, Holm, Kathleen, Goldsmith, Michael-Rock, Tan, Yu-Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2013
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
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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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