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The underlying purpose of the pharmacokinetics study is to investigate the potential whether MeHg and PCBs can induce interactive effects in the developing brain using experimental toxicology and computational modeling. To assess interactive effects between MeHg and PCBs in mice, we focused on two different perspectives: pharmacokinetic interactions and pharmacodynamic interactions. For the former studies, we first investigated pharmacokinetic interactions between two representative PCB congeners. Coadministration of PCB 153 and PCB 126 increased PCB 153 retention in the liver and decreased PCB 153 accumulation in the fat of non-pregnant mice. However, little or no significant pharmacokinetic interactions were observed in lactating mice and suckling pups. To describe pharmacokinetic interactions between PCB 153 and PCB 126, a physiologically-based pharmacokinetic model for PCB 153 disposition was developed. The effects of PCB 126 on the fat content in liver and a diffusion permeation constant in fat were incorporated into the PBPK model. The refined PBPK model adequately described pharmacokinetic interactions. Another PBPK model was constructed to describe the mass transfer of PCB 153 into the developing pup during lactation by incorporating the changes in the volume and blood flow into mammary tissues, and additional mechanistic changes. Then, we investigated pharmacokinetic interactions between MeHg and PCB congeners. The experimental results showed that co-exposure with PCB congeners increased the lactational transfer of MeHg to the pups and compensated the plasma levels of albumin, which decreased by the exposure of MeHg only. A refined PBPK model quantitatively described the pharmacokinetic changes of MeHg by co-exposure with PCBs in both maternal and pup’s tissues and suggested the possible mechanism of pharmacokinetic interactions. For the pharmacokinetic studies, we analyzed protein expression profiles of mural pups exposed to MeHg and/or PCB congeners in cerebellum and hippocampus using proteomics and western blot techniques. The affected proteins were diverse including structural, glycolysis-related, Ca++/calmodulin signal transduction-related, energy balance-related, growth related and stress-related proteins. The expression patterns of proteins were different between single chemical treatment and chemical mixture treatment. Our approach combined experimental toxicology and computational modeling and will ultimately contribute to the innovations of risk assessment in developmental neurotoxicology.