A Physiologically-Based Pharmacokinetic (PBPK) Model With Metabolic Interactions of Chloroform (CHCL3) and Trichloroethylene
Citation:
Eklund, C., M. Evans, H. Yang, Y. Sey, AND J. Simmons. A Physiologically-Based Pharmacokinetic (PBPK) Model With Metabolic Interactions of Chloroform (CHCL3) and Trichloroethylene. Society of Toxicology, San Antonio, TX, March 11 - 15, 2018.
Impact/Purpose:
Exposure to mixtures is frequent, but biologic pathways such as metabolic inhibition, are poorly understood. CHCl3 and TCE are model volatiles frequently co-occurring; combined exposure results in less than additive hepatotoxicity. Here, we explore the underlying metabolic interaction and target tissue dosimetry. Closed chamber data from male F344 rats were used to calibrate PBPK models for CHCl3 alone, TCE alone, and combinations of both chemicals. Our PBPK modeling indicates a need for careful consideration when assessing the risk of combined exposure to chemicals where metabolic interactions result in decreased hepatic metabolism and toxicity and the potential for altered extrahepatic target organ dosimetry and toxicity.
Description:
Exposure to mixtures is frequent, but biologic pathways such as metabolic inhibition, are poorly understood. CHCl3 and TCE are model volatiles frequently co-occurring; combined exposure results in less than additive hepatotoxicity. Here, we explore the underlying metabolic interaction and target tissue dosimetry. Closed chamber data from male F344 rats were used to calibrate PBPK models for CHCl3 alone, TCE alone, and five combinations of both: 500+10 ppm (i.e. 500 ppm CHCl3 with 10 ppm TCE and 500 ppm TCE with 10 ppm CHCl3), 500+500 ppm, 500+2000 ppm, and 1000+1000 ppm. Vmax and km were determined with Least Squares optimization. The 500 ppm exposure for both compounds provided the smallest sum of squares. We then modeled the combined exposures under Michaelis-Menten kinetics and three types of inhibition. Considering the effect of TCE on CHCl3 and that of CHCl3 on TCE, at the most influential chemical concentrations, competitive inhibition improved the fit to data while uncompetitive and noncompetitive inhibition sum-of-squares did not At 10 ppm of either CHCl3 or TCE, the sum-of-squares scores for competitive inhibition and Michaelis-Menten kinetics (i.e. no interaction) were quite close, indicating interaction dose-dependency and the possibility of an interaction threshold as dose increases. As both chemicals are neurotoxic as well as hepatotoxic, we modeled predicted brain Cmax and amount metabolized in liver under no interaction and competitive inhibition. For the effect of CHCl3 on TCE: The presence of 10 ppm CHCl3 had no influence on TCE brain Cmax or amount metabolized in liver when modeled by either no interaction or competitive inhibition. At higher CHCl3 concentrations, TCE brain Cmax was higher and amount metabolized in the liver was lower when modeled with competitive inhibition than no interaction. For the effect of TCE on CHCl3: The presence of 10 ppm TCE had no influence on predicted Cmax or amount metabolized in liver when modeled by either no interaction or competitive inhibition. At higher TCE concentrations, CHCl3 brain Cmax was higher; amount metabolized by liver was lower when modeled with competitive inhibition than no interaction. In summary, our PBPK modeling indicates a need for careful consideration when assessing the risk of combined exposure to chemicals where metabolic interactions result in decreased hepatic metabolism and toxicity and the potential for altered extrahepatic target organ dosimetry and toxicity. (This abstract does reflect not U. S. EPA policy.)