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Safe" doses estimated with standard methods by agencies around the world, whether ADIs, ECNCs, MRLs, TDCs, TCs, TIs, RfCs, or RfDs, should be considered as accurate-but imprecise-estimations of doses or concentrations believed to be without risk to populations of humans (including sensitive subgroups). Restated, these "safe" doses are thought to be below population thresholds for adverse effect, but the degree to which they underestimate the population threshold is generally not known. Part of this imprecision comes from the use of 10-fold default uncertainty factors. We show research and case studies drawn from a large sample of U.S. EPA and Health Canada risk values where uncertainty factors other than a default value of 10-fold were used in the estimation of a RfD, RfC, TDI or TC. Percentages for the use of these "dataderived" factors vary between 3.6% and 47%. In five case studies, we explicitly review the types of data that have been used to support a change in the default value, why the data support a different UF, and what assumptions have been satisfied, replaced, or how the uncertainty was reduced.

Physiologically based pharmacokinetic (PBPK) models have been developed describing the disposition kinetics of nicotine and its major metabolite, cotinine, in man. Separate 9-compartment, flow-limited PBPK models were initially created for nicotine and cotinine. The physiological basis for compartment designation and parameter selection has been provided; chemical-specific tissue-to-blood partition coefficients and elimination rates were derived from published human and animal data. The individual models were tested through simulations of published studies of nicotine and cotinine infusions in man using similar dosing protocols to those reported. Each model adequately predicted the time course of nicotine or cotinine concentrations in the blood and urine following the administration of nicotine or cotinine. These individual models were then linked through the liver compartments to form a nicotine-cotinine model capable of predicting the metabolic production and disposition of cotinine from administered nicotine. The potential for integrating this functional PBPK model with an appropriate pharmacodynamic model for the characterization of nicotine's physiological effects is discussed.