Deriving a data-based interspecies assessment factor using the NOAEL and the benchmark dose approach

Area of Science:

• Toxicology
• Risk Assessment
• Pharmacokinetics

Background:

• Deriving human health-based exposure limits from animal data necessitates accounting for interspecies differences in sensitivity.
• These differences arise from variations in toxicokinetics, toxicodynamics, and body size, with body weight scaling (mg/kg BW/day) and a default assessment factor (AF) of 10 commonly used.

Purpose of the Study:

• To empirically derive data-based assessment factors and allometric scaling powers for interspecies extrapolation.
• To compare the utility of the No Observed Adverse Effect Level (NOAEL) and Benchmark Dose (BMD) approaches in this derivation.

Main Methods:

• Applied both NOAEL and BMD approaches to mouse and rat data to calculate NOAEL and BMD ratios.
• Estimated allometric scaling powers and interspecies AFs based on these ratios.
• Analyzed results using the 95th percentile of ratio distributions and considered probabilistic hazard characterization.

Main Results:

• Confirmed that allometric body weight scaling with a power of approximately 0.7 is appropriate for accounting for body size differences.
• The factor to rescale doses from mg/kg BW to an allometric scale ranged from 1.7 (dogs) to 10 (mice).
• Derived interspecies AFs of 3.1 (BMDL) and 8.3 (NOAEL) were needed, indicating the default AF of 10 may be inadequate, particularly for smaller test species.

Conclusions:

• The default assessment factor of 10 may not adequately protect human health, especially when extrapolating from smaller animal species.
• A data-based assessment factor is smaller when using a BMDL compared to a NOAEL as the point of departure.
• For probabilistic hazard characterization, the geometric standard deviation for the interspecies AF should be approximately 2.0 (BMDL) or 3.4 (NOAEL).