Uncertainty of Estimates of Cancer Risks Derived by Extrapolation from High to Low Doses and from Animals to Humans

Dose-response relationships for hepatic aflatoxin B1-DNA adduct formation in the rat in vivo and in vitro: the use of immunoslot blotting for adduct quantitation

An immunoslot blotting (ISB) method for quantitating aflatoxin B1-DNA adduct levels has been developed and used to examine the relationship between dose and hepatic aflatoxin B1-DNA adduct levels in rats fed aflatoxin B1 (AFB1) in the diet at dose levels of between 0.5 and 10 micrograms/kg/day. The method has also been used to examine the dose-response relationship for adduct formation in precision-cut rat liver slices incubated with AFB1 at concentrations between 0.01 and 2 microM. For the feeding studies, groups of male Fisher F344 rats were given AFB1 in the diet for periods of 1 to 10 weeks and hepatic DNA adduct levels determined using ISB. The time for adduct levels to reach steady-state conditions was determined in animals given approximately 10 micrograms of AFB1/kg/day and steady-state levels at lower concentrations measured. The time course for the accumulation of AFB1-DNA adducts in rat liver slices incubated with AFB1 at 0.5 microM has been investigated and the relationship between adduct formation and AFB1 concentration over a wide concentration range in liver slices has been determined.

Combining uncertainty factors in deriving human exposure levels of noncarcinogenic toxicants

Acceptable levels of human exposure to noncarcinogenic toxicants in environmental and occupational settings generally are derived by reducing experimental no-observed-adverse-effect levels (NOAELs) or benchmark doses (BDs) by a product of uncertainty factors (Barnes and Dourson, Ref. 1). These factors are presumed to ensure safety by accounting for uncertainty in dose extrapolation, uncertainty in duration extrapolation, differential sensitivity between humans and animals, and differential sensitivity among humans. The common default value for each uncertainty factor is 10. This paper shows how estimates of means and standard deviations of the approximately log-normal distributions of individual uncertainty factors can be used to estimate percentiles of the distribution of the product of uncertainty factors. An appropriately selected upper percentile, for example, 95th or 99th, of the distribution of the product can be used as a combined uncertainty factor to replace the conventional product of default factors.