Bioavailability of orally administered drugs can be influenced by a number of factors including release from the formulation, dissolution, stability in the gastrointestinal (GI) environment, permeability through the gut wall and first-pass gut wall and hepatic metabolism. Although there are various enzymes in the gut wall which may contribute to gut first pass metabolism, Cytochrome P450 (CYP) 3A has been shown to play a major role. The efflux transporter P-glycoprotein (P-gp; MDR1/ABCB1) is the most extensively studied drug efflux transporter in the gut and might have a significant role in the regulation of GI absorption. Although not every CYP3A substrate will have a high extent of gut wall first-pass extraction, being a substrate for the enzyme increases the likelihood of a higher first-pass extraction. Similarly, being a P-gp substrate does not necessarily pose a problem with the gut wall absorption however it may reduce bioavailability in some cases (e.g. when drug has low passive permeability). An on-going debate has focused on the issue of the interplay between CYP3A and P-gp such that high affinity to P-gp increases the exposure of drug to CYP3A through repeated cycling via passive diffusion and active efflux, decreasing the fraction of drug that escapes first pass gut metabolism (FG). The presence of P-gp in the gut wall and the high affinity of some CYP3A substrates to this transporter are postulated to reduce the potential for saturating the enzymes, thus increasing gut wall first-pass metabolism for compounds which otherwise would have saturated CYP3A. Such inferences are based on assumptions in the modelling of oral drug absorption. These models should be as mechanistic as possible and tractable using available in vitro and in vivo information. We review, through simulation, this subject and examine the interplay between gut wall metabolism and efflux transporters by studying the fraction of dose absorbed into enterocytes (Fa) and FG via systematic variation of drug characteristics, in accordance with the Biopharmaceutics Classification System (BCS) within one of the most physiological models of oral drug absorption currently available, respectively ADAM. Variables studied included the intrinsic clearance (CLint) and the Michaelis- Menten Constant (Km) for CYP3A4 and P-gp (CLint-CYP3A4 and Km-CYP3A4, CLint-P-gp and Km-P-gp). The impact of CYP3A4 and P-gp intracellular topography were not investigated since a well-stirred enterocyte is assumed within ADAM. An increased CLint-CYP3A4 resulted in a reduced FG whereas an increase in CLint-P-gp resulted in a reduced Fa, but interestingly decreased FG too. The reduction in FG was limited to certain conditions and was modest. Non-linear relationships between various parameters determining the permeability (e.g. Papp, CLint-P-gp, and Km-P-gp) and gut wall metabolism (e.g. CLint-CYP3A4, Km-CYP3A4) resulted in disproportionate changes in FG compared to the magnitude of singular effects. The results suggest that P-gp efflux decreases enterocytic drug concentration for drugs given at reasonably high dose which possess adequate passive apparent permeability (high Papp), by de-saturating CYP3A4 in the gut resulting in a lower FG. However, these findings were observed only in a very limited area of the parameters space matching very few therapeutic drugs (a group with very high metabolism, high turn-over by efflux transporters and low Fa). The systematic approach in this study enabled us to recognise the combination of parameter values where the potential interplay between metabolising enzymes and efflux transporters is expected to be highest, using a realistic range of parameter values taken from an intensive literature search.

Background and Objectives The interplay between liver metabolising enzymes and transporters is a complex process involving system-related parameters such as liver blood perfusion as well as drug attributes including protein and lipid binding, ionisation, relative magnitude of passive and active permeation. Metabolism- and/or transporter-mediated drug–drug interactions (mDDIs and tDDIs) add to the complexity of this interplay. Thus, gaining meaningful insight into the impact of each element on the disposition of a drug and accurately predicting drug–drug interactions becomes very challenging. To address this, an in vitro–in vivo extrapolation (IVIVE)-linked mechanistic physiologically based pharmacokinetic (PBPK) framework for modelling liver transporters and their interplay with liver metabolising enzymes has been developed and implemented within the Simcyp Simulator^®. Methods In this article an IVIVE technique for liver transporters is described and a full-body PBPK model is developed. Passive and active (saturable) transport at both liver sinusoidal and canalicular membranes are accounted for and the impact of binding and ionisation processes is considered. The model also accommodates tDDIs involving inhibition of multiple transporters. Integrating prior in vitro information on the metabolism and transporter kinetics of rosuvastatin (organic-anion transporting polypeptides OATP1B1, OAT1B3 and OATP2B1, sodium-dependent taurocholate co-transporting polypeptide [NTCP] and breast cancer resistance protein [BCRP]) with one clinical dataset, the PBPK model was used to simulate the drug disposition of rosuvastatin for 11 reported studies that had not been used for development of the rosuvastatin model. Results The simulated area under the plasma concentration–time curve (AUC), maximum concentration (C _max) and the time to reach C _max (t _max) values of rosuvastatin over the dose range of 10–80 mg, were within 2-fold of the observed data. Subsequently, the validated model was used to investigate the impact of coadministration of cyclosporine (ciclosporin), an inhibitor of OATPs, BCRP and NTCP, on the exposure of rosuvastatin in healthy volunteers. Conclusion The results show the utility of the model to integrate a wide range of in vitro and in vivo data and simulate the outcome of clinical studies, with implications for their design.