Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.

Application of permeability-limited physiologically-based pharmacokinetic models: part II - prediction of P-glycoprotein mediated drug-drug interactions with digoxin

Digoxin is the recommended substrate for assessment of P-glycoprotein (P-gp)-mediated drug-drug interactions (DDIs) in vivo. The overall aim of our study was to investigate the inhibitory potential of both verapamil and norverapamil on the P-gp-mediated efflux of digoxin in both gut and liver. Therefore, a physiologically-based pharmacokinetic (PBPK) model for verapamil and its primary metabolite was developed and validated through the recovery of observed clinical plasma concentration data for both moieties and the reported interaction with midazolam, albeit a cytochrome P450 3A4-mediated DDI. The validated inhibitor model was then used in conjunction with the model developed previously for digoxin. The range of values obtained for the 10 trials indicated that increases in area under the plasma concentration-time curve (AUC) profiles and maximum plasma concentration observed (Cmax ) values of digoxin following administration of verapamil were more comparable with in vivo observations, when P-gp inhibition by the metabolite, norverapamil, was considered as well. The predicted decrease in AUC and Cmax values of digoxin following administration of rifampicin because of P-gp induction was 1.57- (range: 1.42-1.77) and 1.62-fold (range: 1.53-1.70), which were reasonably consistent with observed values of 1.4- and 2.2-fold, respectively. This study demonstrates the application of permeability-limited models of absorption and distribution within a PBPK framework together with relevant in vitro data on transporters to assess the clinical impact of modulated P-gp-mediated efflux by drugs in development.