Assessing the reliability of PBPK models using data from methyl chloride-exposed, non-conjugating human subjects

Physiologically based pharmacokinetic (PBPK) models are often optimized by adjusting metabolic parameters so as to fit experimental toxicokinetic data. The estimates of the metabolic parameters are then conditional on the assumed values for all other parameters. Meanwhile, the reliability of other parameters, or the structural model, is usually not questioned. Inhalation exposures with human volunteers in our laboratory show that non-conjugators lack metabolic capacity for methyl chloride entirely, and that elimination in these subjects takes place via exhalation only. Therefore, data from these methyl chloride exposures provide an excellent opportunity to assess the general reliability of standard inhalation PBPK models for humans. A hierarchical population PBPK model for methyl chloride was developed. The model was fit to the experimental data in a Bayesian framework using Markov chain Monte Carlo (MCMC) simulation. In a Bayesian analysis, it is possible to merge a priori knowledge of the physiological, anatomical and physicochemical parameters with the information embedded in the experimental toxicokinetic data obtained in vivo. The resulting estimates are both statistically and physiologically plausible. Model deviations suggest that a pulmonary sub-compartment may be needed in order to describe the inhalation and exhalation of volatile adequately. The results also indicate that there may be significant intra-individual variability in the model parameters. To our knowledge, this is the first time that the toxicokinetics of a non-metabolized chemical is used to assess population PBPK parameters. This approach holds promise for more elaborate experiments in order to assess the reliability of PBPK models in general.