External concentrations are frequently more readily quantified, and thus are subject to regulatory or experimental control. However, it is the corresponding internal concentrations, or the concentration of a chemical in blood, plasma, and tissue, that are more directly tied to the toxicological response in the exposed organism. The relationship between internal and external concentrations is quantitatively dictated by pharmacokinetic processes, absorption, distribution, metabolism, and excretion (ADME). Given that many ADME processes are mediated by enzymes or transporters, they are correspondingly saturable at high substrate concentrations, which can lead to nonlinear changes in internal concentration that deviate from being proportional to external concentration. Using a generic, four compartment physiologically based pharmacokinetic (PBPK) model, we analyzed published plasma concentration data for 2,4-dichlorophenoxyacetic acid in rats. These analyses demonstrate how a PBPK modeling approach can be used as an alternative to commonly used statistical methods for analyzing dose proportionality in the internal to external concentration (IEC) relationship. Our analysis indicated that saturable clearance more faithfully characterized available in vivo study results than first-order clearance. In this retrospective analysis, the PBPK model generated a continuous simulation of the IEC relationship across a wide range of doses, which has important advantages over statistical methods that are often restricted to bimodal distinctions of ‘proportional’ versus ‘non-proportional’ dose groups. Beyond retrospective analyses, we assert that a mechanistically credible PBPK model can be developed and used as a tool for integrating available ADME data from short-term in vivo studies or in vitro assays to simulate longer-term exposures. These simulations can be integrated into a weight of evidence approach to the selection of dose magnitude, dose spacing, or sample collection intervals in whole animal studies, which can potentially reduce animal use in longer-term studies.

Interpreting and predicting internal to external concentration relationships using physiologically based pharmacokinetic modeling

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