Estimating Infant and Adult Human Serum Levels of Unconjugated Bisphenol A

Saturday, February 16, 2013
Room 302 (Hynes Convention Center)
Jeffrey Fisher , National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR
Bisphenol A (BPA) is a widespread contaminant found in the food and the environment.  To determine the extent of human exposure to BPA, BPA metabolites are routinely measured in urine, a biological matrix reflecting the accumulated ingested dose of BPA per time period.  Because urine sampling only provides a history of the cumulative exposure to BPA and does not provide measurements of the internal dosimetry of the aglycone BPA, the active form of BPA, computational tools are necessary to predict the serum concentrations of aglycone BPA achieved from ingestion of food contaminated with BPA.  BPA is detoxified by extensive and rapid Phase II metabolism in the small intestine and liver, resulting in low systemic oral- bioavailability.  To account for these critical biological processes, a physiologically based pharmacokinetic (PBPK) model was developed to predict the systemic dosimetry of BPA and its predominant phase II metabolite (BPA-glucuronide) in adults and infants exposed to BPA from food.  BPA and BPA-glucuronide model parameters were derived from an infant and adult monkey BPA PBPK model and limited adult human pharmacokinetic data, where individuals were orally administered deuterated BPA (50-70 µg/kg).  Age-dependent physiological parameters were obtained from the literature.  Steady-state model simulations predicted that median and 90th percentile dietary intakes of BPA would result in aglycone BPA serum concentrations less than a part-per-trillion and BPA glucuronide levels less than a few parts-per-billion, well below the limits of detection for current analytical methods.  The human PBPK model for BPA will be updated as new human pharmacokinetic and biomonitoring data become available and recoded to account for distributions in model parameter values using Monte Carlo methods to predict statistical bounds on serum levels of aglycone BPA.