Serial measurements of serum lipid 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in 36 adults from Seveso, Italy, and three patients from Vienna, Austria, with initial serum lipid TCDD concentrations ranging from 130 to 144,000 ppt, were modeled using a modified version of a previously published toxicokinetic model for the distribution and elimination of dioxins. The original model structure accounted for a concentration-dependent increase in overall elimination rate for TCDD due to nonlinear distribution of TCDD to the liver (secondary to induction of the binding protein CYP1A2), from which elimination takes place via a first-order process. The original model structure was modified to include elimination due to lipid partitioning of TCDD from circulation into the large intestine, based on published human data. We optimized the fit of the modified model to the data by varying the hepatic elimination rate parameter for each of the 39 people. The model fits indicate that there is significant interindividual variability of TCDD elimination efficiency in humans and also demonstrate faster elimination in men compared to women, and in younger vs. older persons. The data and model results indicate that, for males, the mean apparent half-life for TCDD (as reflected in changes in predicted serum lipid TCDD level) ranges from less than 3 years at serum lipid levels above 10,000 ppt to over 10 years at serum lipid levels below 50 ppt. Application of the model to serum sampling data from the cohort of US herbicide-manufacturing workers assembled by the National Institute of Occupational Safety and Health (NIOSH) indicates that previous estimates of peak serum lipid TCDD concentrations in dioxin-exposed manufacturing workers, based on first-order backextrapolations with half-lives of 7-9 years, may have underestimated the maximum concentrations in these workers and other occupational cohorts by several-fold to an order of magnitude or more. Such dose estimates, based on a single sampling point decades after last exposure, are highly variable and dependent on a variety of assumptions and factors that cannot be fully determined, including interindividual variations in elimination efficiency. Dose estimates for these cohorts should be re-evaluated in light of the demonstration of concentration-dependent elimination kinetics for TCDD, and the large degree of uncertainty in back-calculated dose estimates should be explicitly incorporated in quantitative estimates of TCDD's carcinogenic potency based on such data.

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A toxicokinetic model is proposed to predict the time evolution of malathion and its metabolites, mono- and dicarboxylic acids (MCA, DCA) and phosphoric derivatives (dimethyl dithiophosphate [DMDTP], dimethyl thiophosphate [DMTP], and dimethyl phosphate [DMP]) in the human body and excreta, under a variety of exposure routes and scenarios. The biological determinants of the kinetics were established from published data on the in vivo time profiles of malathion and its metabolites in the blood and urine of human volunteers exposed by intravenous, oral, or dermal routes. In the model, body and excreta compartments were used to represent the time varying amounts of each of the following: malathion, MCA, DCA, DMDTP, DMTP, and DMP. The dynamic of intercompartment exchanges was described mathematically by a differential equation system that ensured conservation of mass at all times. The model parameters were determined by statistically adjusting the explicit solution of the differential equations to the experimental human data. Simulations provide a close approximation to kinetic data available in the published literature. When simulating a dermal exposure to malathion, the main route of entry for workers, the model predicts that it takes an average of 11.8 h to recover half of the absorbed dose of malathion eventually excreted in urine as metabolites, compared to 3.2 h following an intravenous injection and 4.0 h after oral administration. This shows that following a dermal exposure, the absorption rate governs the urinary excretion rate of malathion metabolites because the dermal absorption rate is much slower than biotransformation and renal clearance processes. The model served to establish biological reference values for malathion metabolites in urine since it allows links to be made between the absorbed dose of malathion and the time course of cumulative amounts of metabolites excreted in urine. From the no-observed-effect level (NOEL) of 0.61 micromol/kg/day derived from the data of Moeller and Rider (1962), the model predicts corresponding biological reference values for MCA, DCA, and phosphoric derivatives of 44, 13, and 62 nmol/kg, respectively, in 24-h urine samples. The latter were used to assess the health risk of workers exposed to malathion in botanical greenhouses, starting from urinary measurements of MCA and DCA metabolites.

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Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.