Internal Exposure Simulation Based on Exposure Related Dose Estimating Model

Authors

  • Qian Zhang Tianjin Bohai Chemical Industry Group Limited Liability Company Institute of Occupational Health
  • Deyin Huang Tianjin Bohai Chemical Industry Group Limited Liability Company Institute of Occupational Health
  • Mao Liu Nankai University
  • Minyan Li Tianjin Bohai Chemical Industry Group Limited Liability Company Institute of Occupational Health

Keywords:

physiologically based pharmacokinetic model, exposure related dose estimating model, internal exposure, occupational cancer risk

Abstract

In this paper, occupational chemical poisons’ physiologically based pharmacokinetic (PBPK) models are established to simulate metabolic processes in vivo based on exposure simulation software- exposure related dose estimating model (ERDEM). PBPK model establishing progress is described based on the development and utilization of ERDEM. As well known, benzene, 1, 3-butadiene and vinyl chloride are definitely carcinogenic to humans. The study on these carcinogens’ internal exposure has important significance to carcinogenic risk. Internal exposure of these three kinds of chemicals are simulated with parameters of PBPK model, organizations and organism from literature data, which proves ERDEM’s broad applicability. Simulation results are represented by different kinds of results forms such as toxicant concentration in blood changes over time, toxicant average concentration in blood, metabolite amount in target organ changes over time, toxicant concentration in exhaled air changes over time and so on. And the simulation results are verified by comparing with the experimental results in previous literature. The good consistency between simulation results and experimental date reflects that output results of ERDEM are reliable and can be characterized in various forms.

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Published

2021-10-15

How to Cite

Qian Zhang, Deyin Huang, Mao Liu, & Minyan Li. (2021). Internal Exposure Simulation Based on Exposure Related Dose Estimating Model. Journal of Risk Analysis and Crisis Response, 3(4). Retrieved from https://jracr.com/index.php/jracr/article/view/89

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