Population Physiologically Based Pharmacokinetic Modeling for the Human Lactational Transfer of PCB-153 with Consideration of Worldwide Human Biomonitoring Results

• Published in: Environmental health perspectives Vol. 116; no. 12; pp. 1629 - 1634
• Main Authors: Redding, Laurel E., Sohn, Michael D., McKone, Thomas E., Chen, Jein-Wen, Wang, Shu-Li, Hsieh, Dennis P. H., Yang, Raymond S. H.
• Format: Journal Article
• Language: English
• Published: United States National Institute of Environmental Health Sciences. National Institutes of Health. Department of Health, Education and Welfare 01-12-2008; National Institute of Environmental Health Sciences
• Subjects: 54; Adipose tissues; Blood; BODY BURDEN; Body tissues; Breast milk; Chemical hazards; Contamination; DOSIMETRY; Drug design; Environmental Monitoring - methods; Health aspects; Humans; LACTATION; LIPIDS; Measurement; MILK; Milk, Human - chemistry; Modeling; Models, Biological; Pharmacokinetics; Physiologically-based pharmacokinetic modeling, poly-chlorinated biphenyls, PCB 153, Bayesian inference, lactational transfer, body burden, human milk biomonitoring, reverse dosimetry; Pollution; Polychlorinated biphenyls; Polychlorinated Biphenyls - blood; Polychlorinated Biphenyls - pharmacokinetics; Population Surveillance; SIMULATION; STATISTICS; United States; Japan; Taiwan; lactational transfer; human milk biomonitoring; polychlorinated biphenyls; exposure reconstruction; physiologically based pharmacokinetic modeling; body burden; reverse dosimetry; PCB-153
• ISSN: 0091-6765; 1552-9924
• DOI: 10.1289/ehp.11519

Background: One of the most serious human health concerns related to environmental contamination with polychlorinated biphenyls (PCBs) is the presence of these chemicals in breast milk. Objectives: We developed a physiologically based pharmacokinetic model of PCB-153 in women, and predict its transfer via lactation to infants. The model is the first human, population-scale lactational model for PCB-153. Data in the literature provided estimates for model development and for performance assessment. Methods: We used physiologic parameters from a cohort in Taiwan and reference values given in the literature to estimate partition coefficients based on chemical structure and the lipid content in various body tissues. Using exposure data from Japan, we predicted acquired body burden of PCB-153 at an average childbearing age of 25 years and compared predictions to measurements from studies in multiple countries. We attempted one example of reverse dosimetry modeling using our PBPK model for possible exposure scenarios in Canadian Inuits, the population with the highest breast milk PCB-153 level in the world. Results: Forward-model predictions agree well with human biomonitoring measurements, as represented by summary statistics and uncertainty estimates. Conclusion: The model successfully describes the range of possible PCB-153 dispositions in maternal milk, suggesting a promising option for back-estimating doses for various populations.