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Utilizing uncertainty factors in minimal risk levels derivation

H R Pohl1, H G Abadin

  • 1Agency for Toxic Substances and Disease Registry, U.S. Department of Health and Human Services, Atlanta, Georgia 30333, USA.

Regulatory Toxicology and Pharmacology : RTP
|October 1, 1995
PubMed
Summary

The Agency for Toxic Substances and Disease Registry (ATSDR) uses uncertainty factors (UF) to derive minimal risk levels (MRLs). In 30 cases between 1993-1994, ATSDR deviated from default UFs based on chemical-specific toxicity data.

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Area of Science:

  • Environmental Health
  • Toxicology
  • Risk Assessment

Background:

  • The Agency for Toxic Substances and Disease Registry (ATSDR) employs minimal risk levels (MRLs) for public health risk evaluation of hazardous substance exposures.
  • Uncertainty factors (UF) are integral to MRL derivation, with default values of 10 typically used for extrapolations from LOAEL to NOAEL and for inter/intraspecies variability.
  • Deviations from standard UF values are sometimes necessary due to chemical-specific toxicity data.

Purpose of the Study:

  • To document instances where ATSDR's Inter-agency MRL Workgroup departed from default uncertainty factors (UF) during MRL derivation.
  • To present specific examples and the rationales behind these deviations from standard UF values.

Main Methods:

  • Review of MRL derivations conducted by the ATSDR Inter-agency MRL Workgroup from January 1993 to December 1994.

Related Experiment Videos

  • Analysis of cases where substance-specific data justified using UF values other than the default of 10.

    • Main Results:

    • The ATSDR Inter-agency MRL Workgroup derived 46 inhalation and 67 oral MRLs during the study period.
    • In 30 specific instances, the workgroup deviated from the default UF of 10, utilizing chemical-specific data to inform these adjustments.

    Conclusions:

    • ATSDR's methodology allows for flexibility in applying uncertainty factors when warranted by chemical-specific toxicity data.
    • The documented deviations highlight a scientifically-driven approach to MRL derivation, ensuring public health protection.
    • This practice supports the accurate assessment of health risks associated with hazardous substance exposures.