A physiologically based pharmacokinetic model for trichloroethylene (TCE) i
n rodents and humans was calibrated with published toxicokinetic data sets.
A Bayesian statistical framework was used to combine previous information
about the model parameters with the data likelihood, to yield posterior par
ameter distributions. The use of the hierarchical statistical model yielded
estimates of both variability between experimental groups and uncertainty
in TCE toxicokinetics. After adjustment of the model by Markov chain Monte
Carlo sampling, estimates of variability for the animal or human metabolic
parameters ranged from a factor of 1.5-2 (geometric standard deviation [GSD
]). Uncertainty was of the same order as variability for animals and higher
than variability for humans. The model was used to make posterior predicti
ons for several measures of cancer risk. These predictions were affected by
both uncertainties and variability and exhibited GSDs ranging from 2 to 6
in mice and rats and from 2 to 10 for humans.