A PBPK model was developed and evaluated for B[a]P in rats, and a preliminary PBPK model developed for DBC in mice based on pharmacokinetic data generated as part of this research. These models create a foundation for contextualizing the broad base of literature on this class of persistent environmental contaminants. B[a]P is classified as a human carcinogen, and a large body of literature supports its carcinogenicity in rodents and humans. DBC, while much less studied, is considered to be more potent than B[a]P, and has recently been observed to cause transplacental carcinogenesis in mice (Yu et al., 2006
; Castro et al., 2008
). The models we present provide a valuable tool for guiding experimental research on poorly understood aspects of the disposition of DBC and B[a]P, and eventually for elucidating the relationship between animal toxicity experiments and realistic human exposures. By integrating all of the available pharmacokinetic data for these two PAHs into a single framework, we have been able to identify consistent trends as well as discrepancies between data sets and chemicals that may not be obvious when evaluating individual studies. In , the primary data gaps and impediments for continued model development are presented, and these issues are further discussed below.
These models currently describe only the parent compounds, a distinct limitation of model utility, as in both cases carcinogenesis is associated with reactive metabolites of B[a]P and DBC. For B[a]P, there are no pharmacokinetic data on individual metabolites, nor are there adequate in vitro or in vivo data describing individual reactions from its metabolic pathways. For DBC, there is no published information regarding metabolism, and thus the preliminary DBC model relies on kinetic values derived from B[a]P. We are currently working to extend both models to include metabolite sub-models, a process which requires additional pharmacokinetic analyses as well as in vitro metabolic studies describing individual steps of their metabolic pathways. A key to successfully completing these studies will be continued custom synthesis of metabolite standards, as most are not available commercially, as well as continued analytical methods development for these metabolites.
Binding of B[a]P and DBC in blood was described using a simple fractional binding coefficient, rather than a more physiologically realistic description of association and dissociation rate constants and binding capacity. A simplified approach was considered more appropriate based on the limited data available to support description of binding. While binding of B[a]P to various constituents of serum has been explored, only information about fractional binding is currently available (Aarstad et al., 1987
). Standard approaches to measurement of binding kinetics, such as equilibrium dialysis or ultrafiltration, are complicated by the high lipophilicity of B[a]P (log KOW ~ 6.1), which causes profound adsorption to or absorption by plastic materials commonly used in experimentation. We found that increasing fractional binding in the DBC model relative to the B[a]P value greatly improved model predictions. This is consistent with the physical chemical properties of DBC, which is significantly more lipophilic than B[a]P, and thus likely to associate more profoundly with proteins and mobile lipids in the largely aqueous blood compartment. Sensitivity analyses (discussed at length in Supplementary Materials
) indicated that the fractional binding coefficient was the most sensitive parameter in the models by a wide margin, underscoring the importance of experimental work to develop and support this feature.
The simplified description of oral absorption as occurring through a two compartment theoretical GI tract has been commonly employed for lipophilic chemicals (Fisher et al., 2000
). In order to adequately describe the available data on oral absorption of B[a]P, absorption rates had to be fitted to each data set. However, given the variation in experimental dosing regimens, this is not surprising. The data of Foth et al.
(Foth et al., 1988
) used an aqueous vehicle for exposure of Sprague Dawley rats, while that of Uno et al.
(Uno et al., 2004
) used corn oil for exposure of C57BL6/J mice. While inter-species differences could be contributing, the differences in vehicle certainly contribute to the variation in absorption.
Deviation of B[a]P model predictions from observed data occurred in simulation of several data sets. As seen in and , observed terminal phase concentrations of B[a]P in liver and lung were significantly higher than model predictions, possibly indicating macromolecular interactions in these tissues (e.g.
binding). Terminal phase concentrations of B[a]P in blood were also under-predicted for some, but not all, of the available data (e.g., simulations of the lowest available data on IV bolus exposures, the 0.03 mg/kg and 0.002 mg/kg IV exposures of Wiersma & Roth (Wiersma and Roth, 1983b
) and Foth et al.
(Foth et al., 1988
), respectively, were significantly below observed concentrations). While it is possible that our fractional description of binding in blood is insufficient at such low exposures, it is notable that in neither paper were the reliable limits of quantitation reported. This, as well as the distinct plateau visible in each data set, may indicate that measured concentrations were too near background to accurately quantify. The data of Foth et al
. (Foth et al., 1988
), in particular, merits further discussion: our model predictions of each of the reported data sets deviated in some manner and to some degree (). Specific aspects of experimental design (i.e.
, no biological replicates, the use of plastic vascular catheters, and unreported limits of reliable quantitation) would generally have precluded the use of these data in model development and evaluation; however, because of the uniqueness of the data, we chose to include them. Foth et al
are the only researchers to report and compare B[a]P pharmacokinetics after multiple routes of administration. In particular, their investigation of duodenal infusion and oral bolus exposures were invaluable for model development, and were thus used, albeit with caution.
Despite deviations in fit, the B[a]P model is able to reasonably predict concentrations of B[a]P in blood and several tissues of rodents following exposures covering three orders of magnitude and both IV and oral routes of exposure. Additionally, because of the similarities between B[a]P and DBC, we were able to use the B[a]P model as a template for DBC model development.
Until now, pharmacokinetic data for B[a]P have almost exclusively been evaluated using non-compartmental modeling approaches. Non-compartmental analyses facilitate estimation of descriptive parameters such as volumes of distribution, clearance rates, and biological half-lives through empirical descriptions of observed data. However, because they do not consider physiological constraints or biochemical intricacies, such as blood flow, partitioning, or binding, non-compartmental analyses have very limited utility for extrapolation and predictions under varying exposure conditions or in different organisms. PBPK models, such as the ones described here, rely on the incorporation of physiological and biochemical information to develop models that are capable of extrapolation and prediction. This will be especially important as work proceeds to incorporate life-stage information (pregnancy, growth and development) to extrapolate results from transplacental carcinogenicity studies in the future.
A single PBPK model for intravenous dosing of B[a]P in rats has been reported by Roth & Vinegar (Roth and Vinegar, 1990
), but model structure and parameterization were not well described. The model structure was comparable to that reported here, and also used the in vitro
metabolic parameters of Wiersma & Roth (Wiersma and Roth, 1983a
) to describe hepatic and pulmonary metabolism. Partition coefficient values, not specifically reported, were achieved through some method of fitting or estimation to observed data. While binding in blood, lung, and liver was included in the model, the authors did not describe whether it was fractional or dynamic, nor did they report the degree of binding (i.e. parameter values) or the basis for its inclusion. Additional PBPK models for B[a]P in humans have been reported more recently (Chiang and Liao, 2006
; Ciffroy et al., 2011
), and while their structures and parameterization are better described, neither has been evaluated against pharmacokinetic data.
The models we describe here for B[a]P and DBC are thus the first well-explicated PBPK models for high molecular weight PAHs that include extensive evaluation against available pharmacokinetic data in rats and mice, covering a wide range of doses and routes of exposure. During model development, we added only what complexity was needed to describe the available pharmacokinetic data, thereby creating a model for B[a]P with few optimized parameters. The B[a]P model reasonably predicts B[a]P in blood and several tissues following exposures covering three orders of magnitude, as well as both IV and oral routes of exposure. While model predictions were generally adequate, under-prediction of liver and lung concentrations indicate that further research is warranted for these tissues. Disparities between data sets also underscore the necessity of undertaking clarifying pharmacokinetic studies.
Because of their similar physical chemical properties and mechanisms of toxicity, as well as the comparative dearth of available data, the preliminary DBC model is heavily reliant on the B[a]P model for its parameterization. Evaluation against our initial pharmacokinetic data support this approach, as model predictions were generally within a factor of two. Increasing fractional binding of DBC in blood to 97.5% (compared to 90% for B[a]P) brought model predictions in line with observed data, and is plausible based on the higher lipophilicity of DBC. The preliminary DBC model will certainly benefit from additional pharmacokinetic studies and chemical specific parameterization, but in its current iteration is a useful guide for continuing experimental studies, as well as a promising foundation for further model development into additional routes of exposure (specifically inhalation), other organisms including humans, and important life stages (e.g. pregnancy).