BACKGROUND AND OBJECTIVE

The mechanistic framework of physiologically based pharmacokinetic (PBPK) models makes them uniquely suited to hypothesis testing and lineshape analysis, which help provide valuable insights into mechanisms that contribute to the observed concentration-time profiles. The aim of this article is to evaluate the utility of PBPK models for simulating oral lineshapes by optimizing clearance and distribution parameters through fitting observed intravenous pharmacokinetic profiles.

METHODS

A generic PBPK model, built in-house using MATLAB software and incorporating absorption, metabolism, distribution, biliary and renal elimination models, was employed for simulation of the concentration-time profiles of nine marketed drugs with diverse physicochemical and pharmacokinetic profiles and absorption rates determined solely by transcellular or paracellular permeability and solubility. The model is based on easily available physicochemical properties of compounds such as the log P, acid dissociation constant and solubility, and in vitro pharmacokinetic data such as Caco-2 permeability, the fraction of the compound unbound in plasma, and microsomal or hepatocyte intrinsic clearance. Clearance and distribution parameters optimized through simulation of intravenous profiles were used to simulate their corresponding oral profiles, which are determined by a multitude of parameters, both compound-dependent and physiological. Comparison of the simulated and observed oral profiles was done using goodness-of-fit parameters such as the reduced chi(2) statistic. Fold errors were calculated for the area under the plasma concentration-time curve (AUC), maximum plasma concentration (C(max)) and time to reach the C(max) (t(max)), to assess the accuracy of predictions.

RESULTS

The approach of predicting the oral profiles by optimizing the clearance and distribution parameters using the observed intravenous profile seemed to perform well for the nine compounds chosen for the study. The mean fold error for oral pharmacokinetic parameters, such as the C(max), t(max) and AUC, and for lineshape simulation was within 2-fold.

CONCLUSIONS

The validation of the generic PBPK model built in-house demonstrated that as long as the absorption profile of a compound is determined solely by solubility and paracellular or transcellular permeability, the PBPK simulations of oral profiles using optimized parameters from intravenous simulations provide reasonably good agreement with the observed profile with respect to both the lineshape fit and prediction of pharmacokinetic parameters. Therefore, any lineshape mismatch between PBPK simulated and observed oral profiles can be interpreted suitably to gain mechanistic insights into the pharmacokinetic processes that have resulted in the observed lineshape. A strategy has been proposed to identify involvement of carrier-mediated transport; clearance saturation; enterohepatic recirculation of the parent compound; extra-hepatic, extra-gut elimination; higher in vivo solubility than predicted in vitro; drug-induced gastric emptying delays; gut loss and regional variation in gut absorption.