Volume 20, Issue 1 (2023)                   ioh 2023, 20(1): 46-62 | Back to browse issues page

Research code: 50578-99-3-99
Ethics code: IR.TUMS.SPH.REC.1399.221

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Department of Occupational Health Engineering,School of Public Health, Tehran University of Medical Sciences, Tehran,Iran , shahtaheri@tums.ac.ir
Abstract:   (647 Views)
Background and aims:
Given the lack of a developed physiologically based toxicokinetic (PBTK) model for human systemic exposure assessment of methylene diisocyanate (MDI) and prediction of its urinary metabolites, this study aims to develop a PBTK model for exposure risk assessment of MDI.
Methods : In this study, to assess the potential exposure to the MDI, a PBTK model was constructed with parameter uncertainty and variability and calibrated using Bayesian analysis via Markov chain Monte Carlo approach. Exposure reconstruction or reverse dosimetry was performed as an occupational exposure risk assessment through time-kinetic urinary elimination of methylenedianiline (MDA), as the biomarker of MDI, in those exposed to unknown exposure scenarios.
Results: Approximately 15 hours after the start of exposure, the amount of MDA excretion peaked. Understanding simulation results of reverse dosimetry for both exposed persons to the unknown concentration of MDI revealed experienced more systemic exposure than NOAEL (NOAEL = 0.2 ug / l), the exposure concentration (±SD) was 1.58 (±0.856) and 1.005 (±0.705) ug/l for person A and B, respectively. Comparison of predicted results with experimental data shows the model can estimate the kinetic elimination closely to experimental data (R2 = 0.9).
Conclusion: Developed model can be performed to estimate the internal dose of body tissues and understand the risk of occupational exposures by comparing the simulation of biological monitoring with acceptable limit values and determining the potential of external exposure.
Full-Text [PDF 1519 kb]   (296 Downloads)    
Type of Study: Research | Subject: Assessment and risk management
Received: 2021/12/13 | Accepted: 2023/04/4 | Published: 2023/03/30

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