Statistical analysis of Clewell et al. PBPK model of trichloroethylene kinetics.

Abstract

A physiologically based pharmacokinetic model for trichloroethylene (TCE) in 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 parameter 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 [GSDI). Uncertainty was of the same order as variability for animals and higher than variability for humans. The model was used to make posterior predictions 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. The recent development of a comprehensive physiologically based pharmacokinetic (PBPK) model of trichloroethylene (TCE) disposition and metabolism in mice, rats, and humans (1) offers us the opportunity to examine issues of variability and uncertainty for that solvent. In particular, uncertainties in prediction of various cancer dose metrics deserve to be computed, since they could be directly used as input for improved risk assessments.PBPK modeling provides a strong mechanistic basis for prediction of disposition and metabolism of toxicants. Yet much uneasiness remains with the use of these models in toxicology (2). Similarly, as discussed in a recent review and an accompanying commentary, PBPK modeling has not seen the development it promised for therapeutic compounds (3,4). The reason for this essentially lies in the lack of statistical methods for calibrating these models. Because of individual variability and uncertainty, many parameters are difficult to measure accurately even for inbred animal strains. Using input parameters or presenting results in the form of a single value can therefore be very misleading (5). In the absence of rigorous statistical treatment, inference presented by PBPK modeling is largely empirical, hypotheses are left unvalidated, and predictions lack realistic measures of uncertainty. This state of affairs is unfortunate, when considering the consequences (for public health and national welfare) of the decisions made using these models.Obviously, correct statistical treatment of PBPK models is difficult, since these are large nonlinear models with relatively small data sets and a high degree of uncertainty and biological variability (6). It is also essential to respect the fundamental specificity of PBPK models, i.e., their high prior information content, which they provide through the opportunity to use physiological information on parameter values. Yet, although several parameters have physiological meaning and a narrow range of possible values, others-often specific of the com...

Probabilistic methods for addressing uncertainty and variability in biological models: application to a toxicokinetic model

“…Monte Carlo methods are based on a Bayesian statistical approach that involves the use of experimental data to update estimates of a hypothesized "prior" probability distribution for one or more model parameters. Examples of Monte Carlo methods applied to PBPK models can be found in [22][23][24][25][26][27][28][29][30][31].…”

Applications of population approaches in toxicology

“…The same arguments as for animal experiments can be made in favour or the use of population models in that context. For further discussion, the reader is referred to our recent population TK analyses of volunteer exposures to tetrachloroethylene (Bois et al, 1996a; , benzene (Bois et al, 1996b) , trichloroethylene (Bois, 2000b;Bois, 2000a) , or 1,3-butadiene . The inclusion of genotype information in such analyses is straightforward (Johanson et al, 1999) , and should see considerable development in the near future.…”

Dose-response analyses of the carcinogenic effects of trichloroethylene in experimental animals.

“…Administered doses (lifetime average daily doses in mg/kg/day intake) and internal doses based on the pharmacokinetic modeling of Fisher (9), Clewell et al (6), and Bois (29,30) are also shown. These bioassays have been reviewed and their suitability for risk assessment commented on in more detail by Bull (16) and the U.S. EPA (1,2).…”

“…Clewell et al (6) and Bois (29) in his reanalysis of the Clewell pharmacokinetic model have produced estimates of the reactive thiol production in rat and human kidneys at relevant dose levels (Table 10), and these are used in the following quantitative analysis. The Clewell and Bois-C estimates are quite different, almost exactly 100-fold different.…”