PURPOSE: The impact of efflux transporters in intracellular concentrations of a drug can be predicted with modeling techniques. In Part 1, several compartmental models were developed and evaluated. The goal of Part 2 was to apply these models to the characterization and interpretation of saturation kinetic data. METHODS: The compartmental models from Part 1 were used to evaluate a previously published dataset from cell lines expressing varying levels of P-glycoprotein. Kinetic parameters for the transporter were estimated and compared across models. RESULTS: Fits and errors for all compartmental models were identical. All compartmental models predicted more consistent parameters than the Michaelis-Menten model. The 5-compartment model with efflux out of the membrane predicted differential impact of P-gp upon apical versus basolateral drug exposure. Finally, the saturable kinetics of active efflux along with a permeability barrier was modeled to delineate a relationship between intracellular concentration with or without active efflux versus donor concentration. This relationship was not a rectangular hyperbola, but instead was shown to be a quadratic function. CONCLUSIONS: One approach to estimate an in vivo transporter effect is to first model an intracellular Km value from in vitro data, and use this value along with the appropriate tissue transporter expression levels and relative surface area to calculate the relevant apparent Km (or Ki) values. Together with the results from Part 1, these studies suggest that compartmental models can provide a path forward to better utilize in vitro transporter data for in vivo predictions such as physiologically based pharmacokinetic modeling.
PURPOSE: The impact of efflux transporters in intracellular concentrations of a drug can be predicted with modeling techniques. In Part 1, several compartmental models were developed and evaluated. The goal of Part 2 was to apply these models to the characterization and interpretation of saturation kinetic data. METHODS: The compartmental models from Part 1 were used to evaluate a previously published dataset from cell lines expressing varying levels of P-glycoprotein. Kinetic parameters for the transporter were estimated and compared across models. RESULTS:Fits and errors for all compartmental models were identical. All compartmental models predicted more consistent parameters than the Michaelis-Menten model. The 5-compartment model with efflux out of the membrane predicted differential impact of P-gp upon apical versus basolateral drug exposure. Finally, the saturable kinetics of active efflux along with a permeability barrier was modeled to delineate a relationship between intracellular concentration with or without active efflux versus donor concentration. This relationship was not a rectangular hyperbola, but instead was shown to be a quadratic function. CONCLUSIONS: One approach to estimate an in vivo transporter effect is to first model an intracellular Km value from in vitro data, and use this value along with the appropriate tissue transporter expression levels and relative surface area to calculate the relevant apparent Km (or Ki) values. Together with the results from Part 1, these studies suggest that compartmental models can provide a path forward to better utilize in vitro transporter data for in vivo predictions such as physiologically based pharmacokinetic modeling.
Authors: Poulomi Acharya; Michael P O'Connor; Joseph W Polli; Andrew Ayrton; Harma Ellens; Joe Bentz Journal: Drug Metab Dispos Date: 2007-10-29 Impact factor: 3.922
Authors: Daniel Scotcher; Christopher Jones; Maria Posada; Amin Rostami-Hodjegan; Aleksandra Galetin Journal: AAPS J Date: 2016-06-30 Impact factor: 4.009
Authors: Avner Schlessinger; Matthew A Welch; Herman van Vlijmen; Ken Korzekwa; Peter W Swaan; Pär Matsson Journal: Clin Pharmacol Ther Date: 2018-08-30 Impact factor: 6.875