A Physiologically Based Pharmacokinetic Model to Assess the Role of ABC Transporters in Drug Distribution
Frederique Fenneteau, Jun Li, Jacques Turgeon, Fahima Nekka
Faculty of Pharmacy, Université de Montréal, Qc, Canada
Introduction: Drug interactions affecting the expression and/or activity of ATP-Binding Cassette (ABC) transporters may have a significant impact on drug disposition, drug effectiveness or drug toxicity(1-3). Hence, the ability to accurately predict drug disposition over a wide range of conditions of ABC membrane transporter activities is required to better characterize drug pharmacokinetics and pharmacodynamics.
The physiologically based pharmacokinetic (PBPK) modeling, is a well established methodology in the field of risk assessment and environment studies(4, 5). It is now progressively used at variant stages of drug discovery and development. However, existing PBPK models have not been designed to characterize distribution of ABC transporters drug substrates in tissues, mainly because of the restricted access to ABC transporters-related physiological data and parameters.
The most studied ABC membrane transporter is P-glycoprotein (P-gp), a multidrug resistance (mdr) protein found to be expressed in normal tissues, such as the intestine, kidneys, liver, brain, testis, ovaries, placenta, and heart. These numerous locations suggest an important role for P-gp in drug absorption and excretion and in limitation of drug penetration into target tissues(6).
Objective: The main objective of our study was to develop an innovative model that takes into account the involvement of ABC transporter activities in different tissues, in order to improve prediction of drug distribution in the various conditions surrounding ABC transporter activities.
Methods: A PBPK model was developed for wild type mice and mice lacking mdr1 genes to which a 5mg/kg dose of 3H-domperidone, a P-gp substrate, has been administered intravenously. Blood, plasma, hepatic, renal, cerebral and cardiac tissues were collected from each animal and were analysed for radioactivity by liquid scintillation spectroscopy. Metabolite profiling of blood, brain, liver and left ventricle samples, collected at 4 and 120 min post dose, were analyzed by HPLC using a radiometric detection.
In the PBPK model, drug distribution into tissues where ABC transporters have a significant protective or excretive function was represented by variants of perfusion or permeability rate limited models that we developed, whereas drug distribution into other tissues was represented by a well-stirred model with partition coefficient estimated from the method developed by Poulin and Theil(7).
Physico-chemical properties of domperidone and physiological mice-related parameters were extracted from the literature(7, 8, 9). Input parameters related to the activity of P-gp in mice tissues and input parameters related to the domperidone diffusion rate through tissue membrane were obtained by developing a step-by-step procedure of in vitro-in vivo extrapolations. About 500 multivariate log-normal Monte-Carlo simulations were also performed to account for the uncertainty and variability of input parameters and their influence on the following model outputs obtained on each tissue: Cmax and AUC0-tlast. The measure of input-output sensitivity was performed using the partial rank correlation coefficient (PRCC) concept which has been designed for correlated inputs (10).
Results: T
The comparison of PBPK model simulations with experimental data of concentration-time profiles in mice plasma and tissues provided mechanistic information on the involvement of additional efflux transporters in domperidone distribution into brain tissue as well as the involvement of influx membrane transporters in its distribution in heart tissue. The sensitivity analysis performed on the present PBPK model, based on Monte-Carlo simulations and PRCC concept, showed that the plasma AUC values were strongly affected by the metabolic parameters Km, Vmax and fup. For heart tissue, the most important variables affecting the outputs were parameters related to influx and efflux transport. For brain tissue, the outputs parameters were mainly affected by fup, by the parameters related to the P-gp efflux transport.
Conclusion: This new physiologically based pharmacokinetic model explains and describes domperidone distribution mechanisms in various tissues in the absence or presence of P-gp activity. The herein described PBPK model is novel and unique while defined in general terms that can be applied to other drugs and transporters.
References:
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