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Related Experiment Videos

Reassessing benzene risks using internal doses and Monte-Carlo uncertainty analysis

L A Cox1

  • 1Cox Associates, Denver, Colorado 80218, USA. tcoxdenver@aol.com

Environmental Health Perspectives
|December 1, 1996
PubMed
Summary

Physiologically based pharmacokinetic (PBPK) models reevaluate human cancer risks from benzene. New analyses suggest benzene excess risk may be nonexistent at low doses, aligning with biological data.

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Area of Science:

  • Toxicology
  • Environmental Health
  • Risk Assessment

Background:

  • Human cancer risks from benzene are typically estimated using epidemiological and animal bioassay data.
  • Previous risk assessments relied on interspecies dose conversions, potentially introducing uncertainties.

Purpose of the Study:

  • To reexamine animal-based benzene risk assessments using physiologically based pharmacokinetic (PBPK) models.
  • To improve the accuracy of low-dose human risk estimations for benzene exposure.

Main Methods:

  • Utilized PBPK models to simulate benzene metabolism in animals and humans.
  • Applied nonlinear regression (Michaelis-Menten) and multistage models to internal dose data.
  • Conducted Monte-Carlo uncertainty analysis and incorporated pharmacokinetic and hematotoxic data.

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Main Results:

  • PBPK models accurately predicted internal benzene metabolite doses in mice.
  • Refitting models to internal doses resulted in a cubic dose-response curve for mice, reducing low-dose risk estimates.
  • Using human PBPK model-derived internal doses lowered estimated human risks at low exposure levels.
  • Sensitivity analyses confirmed the robustness of nonlinear dose-response findings.

Conclusions:

  • Benzene risk assessment using PBPK models suggests reduced human risk at low doses compared to previous methods.
  • The probability of a positive low-dose slope for excess risk is estimated at approximately 10%.
  • Pharmacokinetic and hematotoxic data support the hypothesis that low inhaled benzene concentrations may not pose an excess risk.