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An alternate metabolic hypothesis for a binary mixture of trichloroethylene and carbon tetrachloride: application of physiologically based pharmacokinetic (PBPK) modeling in rats.
Citation:
Epps, P., J. Garcia, E. Lee, A. Walls, D. Frank, D. Eklund, AND M. V. EVANS. An alternate metabolic hypothesis for a binary mixture of trichloroethylene and carbon tetrachloride: application of physiologically based pharmacokinetic (PBPK) modeling in rats. Presented at Research Experience for Undergraduates Program- NC State Univ, Raleigh, NC, August 02 - 06, 2010.
Impact/Purpose:
Carbon tetrachloride (CC4) and trichloroethylene (TCE) are hepatotoxic volatile organic compounds (VOCs) and environmental contaminants. The goal of this project was to study co-exposure to both chemicals, since both are found together in many contaminated sites.
Description:
Carbon tetrachloride (CC4) and trichloroethylene (TCE) are hepatotoxic volatile organic compounds (VOCs) and environmental contaminants. Previous physiologically based pharmacokinetic (PBPK) models describe the kinetics ofindividual chemical disposition and metabolic clearance for target organs of concern. Metabolism of both chemicals in the liver is critical for biological damage to occur. The goal of this project was to study co-exposure to both chemicals, since both are found together in many contaminated sites. Closed chamber inhalation data from the co-exposure of CC4 and TCE is a technique designed to quantify metabolism for most solvents. Gas-uptake results in rats suggest a simultaneous increase of CC4 metabolism and inhibition of TCE metabolism. The kinetics of the main enzyme CYP2E1 are mathematically described by considering the possibility of two binding sites since the kinetics of CYP2E1 cannot be described by competitive inhibition. This interaction is modeled using a reaction mechanism that describes both activation and inhibition by incorporating alpha and beta descriptor constants. These constants, along with the maximum metabolic velocity and affmity for each chemical, are optimized using the Nelder-Mead simplex method within Matlab. Preliminary modeling results are consistent with the idea ofmultiple sites describing both the metabolic increase and inhibition by the same enzyme. The modeling results help explain the heightened metabolic flexibility of this unique liver enzyme. Also, sensitivity analysis ofthe model is used to prioritize its sensitivity coefficients to identified parameters. (This abstract does not reflect EPA policy).