Impact of Biological and Environmental Variabilities on Biological Monitoring—An Approach Using Toxicokinetic Models

A. Berthet, A. de Batz, R. Tardif, G. Charest-Tardif, G. Truchon, D. Vernez, P. O. Droz
2010 Journal of Occupational and Environmental Hygiene  
Berthet, A. ; de Batz, A. ; Tardif, R. ; Charest-Tardif, G. ; Truchon, G. ; Vernez, D. ; Droz, P.O. Impact of biological and environmental variabilities on biological monitoring: an approach using toxicokinetic models. SUMMARY Context. Biological monitoring of occupational exposure is characterized by important variability, due to both variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a
more » ... is important for a dependable application of biological monitoring. The purpose of this work was to describe this variability, using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. Methods. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physico-chemical and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Results and Conclusion. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated to changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the fourteen chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hours) this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased.
doi:10.1080/15459620903530052 pmid:20063230 fatcat:we2sdaskizhc5o7j2jp2grrhoe