Limits...
Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation.

McNally K, Cotton R, Cocker J, Jones K, Bartels M, Rick D, Price P, Loizou G - J Toxicol (2012)

Bottom Line: There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals.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.

View Article: PubMed Central - PubMed

Affiliation: Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UK.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

A comparison of 5 CV biomarker profiles corresponding to parameter sets sampled from the priors and reliable CV measurements.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3376947&req=5

fig5: A comparison of 5 CV biomarker profiles corresponding to parameter sets sampled from the priors and reliable CV measurements.

Mentions: An infinite family of parameter sets, which are inputs to the PBPK model, are defined by the (prior) probability distributions on model parameters. Each parameter set is used to overwrite the initial (default) parameters, thereby constituting a different PBPK model. In Figure 5 the reliable CV measurements and the biomarker profiles corresponding to 5 parameter sets drawn from the prior distributions of the model parameters are shown. Each PBPK model specified by a particular parameter set is unique; however, very different sets of parameters may define similar PBPK models (with respect to specific model outputs). The objective of the reverse dosimetry is to calibrate or tune the unknown parameters of the model θ and the exposure concentration λ such that the observational data and model predictions are in close agreement. Convergence to a unique solution was not possible (due to both measurement error and model inadequacy); however, calibration should result in a substantial reduction in the domain of the family of models that are consistent with measurements. Formally, inference was achieved through application of the Bayes theorem. The posterior distribution results in a narrower range of biomarker profiles than that depicted in Figure 5.


Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation.

McNally K, Cotton R, Cocker J, Jones K, Bartels M, Rick D, Price P, Loizou G - J Toxicol (2012)

A comparison of 5 CV biomarker profiles corresponding to parameter sets sampled from the priors and reliable CV measurements.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3376947&req=5

fig5: A comparison of 5 CV biomarker profiles corresponding to parameter sets sampled from the priors and reliable CV measurements.
Mentions: An infinite family of parameter sets, which are inputs to the PBPK model, are defined by the (prior) probability distributions on model parameters. Each parameter set is used to overwrite the initial (default) parameters, thereby constituting a different PBPK model. In Figure 5 the reliable CV measurements and the biomarker profiles corresponding to 5 parameter sets drawn from the prior distributions of the model parameters are shown. Each PBPK model specified by a particular parameter set is unique; however, very different sets of parameters may define similar PBPK models (with respect to specific model outputs). The objective of the reverse dosimetry is to calibrate or tune the unknown parameters of the model θ and the exposure concentration λ such that the observational data and model predictions are in close agreement. Convergence to a unique solution was not possible (due to both measurement error and model inadequacy); however, calibration should result in a substantial reduction in the domain of the family of models that are consistent with measurements. Formally, inference was achieved through application of the Bayes theorem. The posterior distribution results in a narrower range of biomarker profiles than that depicted in Figure 5.

Bottom Line: There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals.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.

View Article: PubMed Central - PubMed

Affiliation: Health and Safety Laboratory, Harpur Hill, Buxton, Derbyshire SK17 9JN, UK.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus