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Dose Reconstruction Of Di-2-Ethylhexyl Phthalate Using A Simple Pharmacokinetic Model [Manuscript]
Citation:
LORBER, M. AND A. Calafat. Dose Reconstruction Of Di-2-Ethylhexyl Phthalate Using A Simple Pharmacokinetic Model [Manuscript]. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, 120(12):1705-1710, (2012).
Impact/Purpose:
We sought to better understand the timing and extent of DEHP exposure which would cause the appearance of the metabolites in urine by “reconstructing” the DEHP dose using a simple pharmacokinetic model.
Description:
Background In 2005, eight adults provided full volumes and times of urine voids during one normal work week. These samples were analyzed for four di-2-ethylhexyl phthalate (DEHP) metabolites. Participants also provided diary information on their diet, driving, and out¬door activities during the study week. Objectives We sought to better understand the timing and extent of DEHP exposure which would cause the appearance of the metabolites in urine by “reconstructing” the DEHP dose using a simple pharmacokinetic model. Methods We used a model previously calibrated on a single person self-dosed with DEHP in conjunction with the experimental data. We found times and doses of DEHP which resulted in a best fit of predicted and measured urinary concentrations of the metabolites using a simple trial-and-error method. Results The average daily mean and median reconstructed DEHP doses were 10.5 and 5.0 µg/kg-day, respectively. The highest single modeled dose of 70 µg/kg occurred when one study participant reported consuming a bagel with egg and sausage, and coffee, purchased at a gas station. About two thirds of all modeled intake events occurred near the time of reported food or beverage consumption. Twenty percent of the modeled DEHP exposure occurred between the hours of 10 pm and 5 am. Conclusions Dose reconstruction using pharmacokinetic models in conjunction with biomonitoring data, diary information, and other related data can provide a powerful means to define timing, magnitude, and possible sources of exposure to a given contaminant.