Reconstruction of exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol using computational fluid dynamics, physiologically based toxicokinetics and statistical modeling

This study employed computational fluid dynamics (CFD), physiologically based toxicokinetics (PBTK), and statistical modeling to reconstruct exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol. By utilizing a validated CFD model, human respiratory deposition of MDI aerosol in differe...

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Bibliographic Details
Published in:Inhalation toxicology 2023-10, Vol.35 (11-12), p.285-299
Main Authors: Mozaffari, Sajjad, Bayatian, Majid, Hsieh, Nan-Hung, Khadem, Monireh, Garmaroudi, Amir Abbasi, Ashrafi, Khosro, Shahtaheri, Seyed Jamaleddin
Format: Article
Language:English
Subjects:
Aerosols
Animals
Humans
Hydrodynamics
Isocyanates - toxicity
Rats
Toxicokinetics
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Summary:This study employed computational fluid dynamics (CFD), physiologically based toxicokinetics (PBTK), and statistical modeling to reconstruct exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol. By utilizing a validated CFD model, human respiratory deposition of MDI aerosol in different workload conditions was investigated, while a PBTK model was calibrated using experimental rat data. Biomonitoring data and Markov Chain Monte Carlo (MCMC) simulation were utilized for exposure assessment. Deposition fraction of MDI in the respiratory tract at the light, moderate, and heavy activity were 0.038, 0.079, and 0.153, respectively. Converged MCMC results as the posterior means and prior values were obtained for several PBTK model parameters. In our study, we calibrated a rat model to investigate the transport, absorption, and elimination of 4,4'-MDI inhalation exposure. The calibration process successfully captured experimental data in the lungs, liver, blood, and kidneys, allowing for a reasonable representation of MDI distribution within the rat model. Our calibrated model also represents MDI dynamics in the bloodstream, facilitating the assessment of bioavailability. For human exposure, we validated the model for recent and long-term MDI exposure using data from relevant studies. Our computational models provide reasonable insights into MDI exposure, contributing to informed risk assessment and the development of effective exposure reduction strategies.
ISSN:0895-8378
1091-7691
DOI:10.1080/08958378.2023.2285772