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A physiologically-based kinetic (PBK) model for work-related diisocyanate exposure: Relevance for the design and reporting of biomonitoring studies

•We developed a PBK model for occupational diisocyanate exposure.•Sensitivity analysis quantified the impact of factors on modelled urinary levels.•This PBK model helps define relevant factors for interpreting biomonitoring data.•Sampling time relative to task and frequency of urination are importan...

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Bibliographic Details
Published in:Environment international 2023-04, Vol.174, p.107917-107917, Article 107917
Main Authors: Scholten, B., Westerhout, J., Pronk, A., Stierum, R., Vlaanderen, J., Vermeulen, R., Jones, K., Santonen, T., Portengen, L.
Format: Article
Language:English
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Summary:•We developed a PBK model for occupational diisocyanate exposure.•Sensitivity analysis quantified the impact of factors on modelled urinary levels.•This PBK model helps define relevant factors for interpreting biomonitoring data.•Sampling time relative to task and frequency of urination are important. Diisocyanates are highly reactive substances and known causes of occupational asthma. Exposure occurs mainly in the occupational setting and can be assessed through biomonitoring which accounts for inhalation and dermal exposure and potential effects of protective equipment. However the interpretation of biomonitoring data can be challenging for chemicals with complex kinetic behavior and multiple exposure routes, as is the case for diisocyanates. To better understand the relation between external exposure and urinary concentrations of metabolites of diisocyanates, we developed a physiologically based kinetic (PBK) model for methylene bisphenyl isocyanate (MDI) and toluene di-isocyanate (TDI). The PBK model covers both inhalation and dermal exposure, and can be used to estimate biomarker levels after either single or chronic exposures. Key parameters such as absorption and elimination rates of diisocyanates were based on results from human controlled exposure studies. A global sensitivity analysis was performed on model predictions after assigning distributions reflecting a mixture of parameter uncertainty and population variability. Although model-based predictions of urinary concentrations of the degradation products of MDI and TDI for longer-term exposure scenarios compared relatively well to empirical results for a limited set of biomonitoring studies in the peer-reviewed literature, validation of model predictions was difficult because of the many uncertainties regarding the precise exposure scenarios that were used. Sensitivity analyses indicated that parameters with a relatively large impact on model estimates included the fraction of diisocyanates absorbed and the binding rate of diisocyanates to albumin relative to other macro molecules.We additionally investigated the effects of timing of exposure and intermittent urination, and found that both had a considerable impact on estimated urinary biomarker levels. This suggests that these factors should be taken into account when interpreting biomonitoring data and included in the standard reporting of isocyanate biomonitoring studies.
ISSN:0160-4120
1873-6750
DOI:10.1016/j.envint.2023.107917