Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation
There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biolog...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Toxicology |
| Online Access: | http://dx.doi.org/10.1155/2012/760281 |
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| _version_ | 1832552776456994816 |
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| author | Kevin McNally Richard Cotton John Cocker Kate Jones Mike Bartels David Rick Paul Price George Loizou |
| author_facet | Kevin McNally Richard Cotton John Cocker Kate Jones Mike Bartels David Rick Paul Price George Loizou |
| author_sort | Kevin McNally |
| collection | DOAJ |
| description | There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biological guidance values. Exposure reconstruction or reverse dosimetry is the retrospective interpretation of external exposure consistent with biomonitoring data. We investigated the integration of physiologically based pharmacokinetic modelling, global sensitivity analysis, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of inhalation exposure to m-xylene. We used exhaled breath and venous blood m-xylene and urinary 3-methylhippuric acid measurements from a controlled human volunteer study in order to evaluate the ability of our computational framework to predict known inhalation exposures. We also investigated the importance of model structure and dimensionality with respect to its ability to reconstruct exposure. |
| format | Article |
| id | doaj-art-63308a8bcaa84661b0e47f72c9f0eb2a |
| institution | Kabale University |
| issn | 1687-8191 1687-8205 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Toxicology |
| spelling | doaj-art-63308a8bcaa84661b0e47f72c9f0eb2a2025-02-03T05:57:53ZengWileyJournal of Toxicology1687-81911687-82052012-01-01201210.1155/2012/760281760281Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo SimulationKevin McNally0Richard Cotton1John Cocker2Kate Jones3Mike Bartels4David Rick5Paul Price6George Loizou7Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UKHealth and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UKHealth and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UKHealth and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UKToxicology & Environmental Research and Consulting, The Dow Chemical Company, Midland, MI 48674, USAToxicology & Environmental Research and Consulting, The Dow Chemical Company, Midland, MI 48674, USAToxicology & Environmental Research and Consulting, The Dow Chemical Company, Midland, MI 48674, USAHealth and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UKThere are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biological guidance values. Exposure reconstruction or reverse dosimetry is the retrospective interpretation of external exposure consistent with biomonitoring data. We investigated the integration of physiologically based pharmacokinetic modelling, global sensitivity analysis, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of inhalation exposure to m-xylene. We used exhaled breath and venous blood m-xylene and urinary 3-methylhippuric acid measurements from a controlled human volunteer study in order to evaluate the ability of our computational framework to predict known inhalation exposures. We also investigated the importance of model structure and dimensionality with respect to its ability to reconstruct exposure.http://dx.doi.org/10.1155/2012/760281 |
| spellingShingle | Kevin McNally Richard Cotton John Cocker Kate Jones Mike Bartels David Rick Paul Price George Loizou Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation Journal of Toxicology |
| title | Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation |
| title_full | Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation |
| title_fullStr | Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation |
| title_full_unstemmed | Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation |
| title_short | Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation |
| title_sort | reconstruction of exposure to m xylene from human biomonitoring data using pbpk modelling bayesian inference and markov chain monte carlo simulation |
| url | http://dx.doi.org/10.1155/2012/760281 |
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