Literature DB >> 17108893

Reverse dosimetry: interpreting trihalomethanes biomonitoring data using physiologically based pharmacokinetic modeling.

Yu-Mei Tan1, Kai H Liao, Harvey J Clewell.   

Abstract

Biomonitoring data provide evidence of exposure of environmental chemicals but are not, by themselves, direct measures of exposure. To use biomonitoring data in understanding exposure, physiologically based pharmacokinetic (PBPK) modeling can be used in a reverse dosimetry approach to assess a distribution of exposures possibly associated with specific blood or urine levels of compounds. Reverse dosimetry integrates PBPK modeling with exposure pattern characterization, Monte Carlo analysis, and statistical tools to estimate a distribution of exposures that are consistent with biomonitoring data in a population. The present study used an existing PBPK model for chloroform as a generic framework to develop PBPK models for other trihalomethanes (THMs). Using Monte Carlo sampling techniques, probabilistic information about pharmacokinetics and exposure patterns was included to estimate distributions of THMs concentrations in blood in relation to various exposure patterns in a diverse population. In addition, the possibility of inhibition of hepatic metabolism among THMs was evaluated under the scenarios of household exposure. These studies demonstrated how PBPK modeling can be used as a tool to estimate a population distribution of exposures that could have resulted in particular biomonitoring results. When toxicity level is known, this tool can also be used to estimate proportion of population above levels associated with health risk.

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Year:  2006        PMID: 17108893     DOI: 10.1038/sj.jes.7500540

Source DB:  PubMed          Journal:  J Expo Sci Environ Epidemiol        ISSN: 1559-0631            Impact factor:   5.563


  33 in total

1.  Reconstructing population exposures to environmental chemicals from biomarkers: challenges and opportunities.

Authors:  Panos G Georgopoulos; Alan F Sasso; Sastry S Isukapalli; Paul J Lioy; Daniel A Vallero; Miles Okino; Larry Reiter
Journal:  J Expo Sci Environ Epidemiol       Date:  2008-03-26       Impact factor: 5.563

2.  Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.

Authors:  Caroline L Ring; Robert G Pearce; R Woodrow Setzer; Barbara A Wetmore; John F Wambaugh
Journal:  Environ Int       Date:  2017-06-16       Impact factor: 9.621

3.  Occurrence of disinfection by-products in tap water distribution systems and their associated health risk.

Authors:  Jin Lee; Eun-Sook Kim; Bang-Sik Roh; Seog-Won Eom; Kyung-Duk Zoh
Journal:  Environ Monit Assess       Date:  2013-02-28       Impact factor: 2.513

Review 4.  In vitro to in vivo extrapolation for high throughput prioritization and decision making.

Authors:  Shannon M Bell; Xiaoqing Chang; John F Wambaugh; David G Allen; Mike Bartels; Kim L R Brouwer; Warren M Casey; Neepa Choksi; Stephen S Ferguson; Grazyna Fraczkiewicz; Annie M Jarabek; Alice Ke; Annie Lumen; Scott G Lynn; Alicia Paini; Paul S Price; Caroline Ring; Ted W Simon; Nisha S Sipes; Catherine S Sprankle; Judy Strickland; John Troutman; Barbara A Wetmore; Nicole C Kleinstreuer
Journal:  Toxicol In Vitro       Date:  2017-12-05       Impact factor: 3.500

5.  Occurrences and changes of disinfection by-products in small water supply systems.

Authors:  Shakhawat Chowdhury
Journal:  Environ Monit Assess       Date:  2017-12-20       Impact factor: 2.513

6.  Predicting human exposure and risk from chlorinated indoor swimming pool: a case study.

Authors:  Shakhawat Chowdhury
Journal:  Environ Monit Assess       Date:  2015-07-12       Impact factor: 2.513

7.  In vitro screening for population variability in toxicity of pesticide-containing mixtures.

Authors:  Nour Abdo; Barbara A Wetmore; Grace A Chappell; Damian Shea; Fred A Wright; Ivan Rusyn
Journal:  Environ Int       Date:  2015-09-19       Impact factor: 9.621

Review 8.  Nanotechnology-based electrochemical sensors for biomonitoring chemical exposures.

Authors:  Richard C Barry; Yuehe Lin; Jun Wang; Guodong Liu; Charles A Timchalk
Journal:  J Expo Sci Environ Epidemiol       Date:  2008-11-19       Impact factor: 5.563

9.  Contribution of inorganic arsenic sources to population exposure risk on a regional scale.

Authors:  Wei-Chun Chou; Jein-Wen Chen; Chung-Min Liao
Journal:  Environ Sci Pollut Res Int       Date:  2016-04-06       Impact factor: 4.223

10.  Exposure as part of a systems approach for assessing risk.

Authors:  Linda S Sheldon; Elaine A Cohen Hubal
Journal:  Environ Health Perspect       Date:  2009-04-08       Impact factor: 9.031

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