Masoud Jamei

The Simcyp® Population-based ADME Simulator

The Simcyp® population-based absorption, distribution, metabolism and excretion simulator is a platform and database for ‘bottom-up’ mechanistic modelling and simulation of the processes of oral absorption, tissue distribution, metabolism and excretion of drugs and drug candidates in healthy and disease populations. It combines experimental data generated routinely during preclinical drug discovery and development from in vitro enzyme and cellular systems and relevant physicochemical attributes of compound and dosage form with demographic, physiological and genetic information on different patient populations. The mechanistic approach implemented in the Simcyp Simulator allows simulation of complex absorption, distribution, metabolism and excretion outcomes, particularly those involving multiple drug interactions, parent drug and metabolite profiles and time- and dose-dependent phenomena such as auto-induction and auto-inhibition. This review describes the framework and organisation of the simulator and how it combines the different categories of information.

Population-based mechanistic prediction of oral drug absorption.

The bioavailability of drugs from oral formulations is influenced by many physiological factors including gastrointestinal fluid composition, pH and dynamics, transit and motility, and metabolism and transport, each of which may vary with age, gender, race, food, and disease. Therefore, oral bioavailability, particularly of poorly soluble and/or poorly permeable compounds and those that are extensively metabolized, often exhibits a high degree of inter- and intra-individual variability. While several models and algorithms have been developed to predict bioavailability in an average person, efforts to accommodate intrinsic variability in the component processes are less common. An approach that incorporates such variability for human populations within a mechanistic framework is described together with examples of its application to drug and formulation development.

Cytochrome P450 Turnover: Regulation of Synthesis and Degradation, Methods for Determining Rates, and Implications for the Prediction of Drug Interactions

In vivo enzyme levels are governed by the rates of de novo enzyme synthesis and degradation. A current lack of consensus on values of the in vivo turnover half-lives of human cytochrome P450 (CYP) enzymes places a significant limitation on the accurate prediction of changes in drug concentration-time profiles associated with interactions involving enzyme induction and mechanism (time)-based inhibition (MBI). In the case of MBI, the full extent of inhibition is also sensitive to values of enzyme turnover half-life. We review current understanding of CYP regulation, discuss the pros and cons of various in vitro and in vivo approaches used to estimate the turnover of specific CYPs and, by simulation, consider the impact of variability in estimates of CYP turnover on the prediction of enzyme induction and MBI in vivo. In the absence of consensus on values for the in vivo turnover half-lives of key CYPs, a sensitivity analysis of predictions of the pharmacokinetic effects of enzyme induction and MBI to these values should be an integral part of the modelling exercise, and the selective use of values should be avoided.

Physiologically based mechanistic modelling to predict complex drug–drug interactions involving simultaneous competitive and time-dependent enzyme inhibition by parent compound and its metabolite in both liver and gut—The effect of diltiazem on the time-course of exposure to triazolam

AIM To predict the magnitude of metabolic drug-drug interaction (mDDI) between triazolam and diltiazem and its primary metabolite N-desmethyldiltiazem (MA). METHODS Relevant in vitro metabolic and inhibitory data were incorporated into a mechanistic physiologically based pharmacokinetic model within Simcyp (Version 9.1) to simulate the time-course of changes in active CYP3A4 content in gut and liver and plasma concentrations of diltiazem, MA and triazolam in a virtual population with characteristics related to in vivo studies. RESULTS The predicted median increases in AUC(0,infinity) of triazolam, which ranged from 3.9 to 9.5 for 20 simulated trials (median 5.9), were within 1.5-fold of the observed median value (4.4) in 14 of the trials. Considering the effects of diltiazem only and not those of MA, and ignoring auto-inhibition of MA metabolism and inhibition of its metabolism by diltiazem, resulted in lower increases in triazolam exposure (AUC ratios of 1.5-2.0 (median 1.7) and 2.7-5.3 (median 3.4), respectively). CONCLUSION Prediction of mDDIs involving diltiazem requires consideration of both competitive and time-dependent inhibition in gut and liver by both diltiazem and MA, as well as the complex interplay between the two moieties with respect to mutual inhibition of parent compound and its metabolite.

ITC Recommendations for Transporter Kinetic Parameter Estimation and Translational Modeling of Transport‐Mediated PK and DDIs in Humans

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter‐knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter‐mediated pharmacokinetics and drug–drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science.

Interplay of Metabolism and Transport in Determining Oral Drug Absorption and Gut Wall Metabolism : A Simulation Assessment Using the "Advanced Dissolution, Absorption, Metabolism (ADAM)" Model

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 (F(G)). 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 (F(a)) and F(G) 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 (C(Lint-CYP3A4) and K(m-CYP3A4), CL(int-P-gp) and K(m-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 F(G) whereas an increase in C(Lint-P-gp) resulted in a reduced F(a), but interestingly decreased F(G) too. The reduction in FG was limited to certain conditions and was modest. Non-linear relationships between various parameters determining the permeability (e.g. P(app), C(Lint-P-gp,) and K(m-P-gp)) and gut wall metabolism (e.g. C(Lint-CYP3A4,) K(m-CYP3A4)) resulted in disproportionate changes in F(G) 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 permeability (high P(app)), by de-saturating CYP3A4 in the gut resulting in a lower F(G). 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 F(a)). The systematic approach in this study enabled us to recognise the combination of parameters 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.

PBPK modelling of inter-individual variability in the pharmacokinetics of environmental chemicals.

Generic PBPK models, applicable to a large number of substances, coupled to parameter databases and QSAR modules, are now available for predictive modelling of inter-individual variability in the absorption, distribution, metabolism and excretion of environmental chemicals. When needed, Markov chain Monte Carlo methods and multilevel population models can be jointly used for a Bayesian calibration of a PBPK model, to improve our understanding of the determinants of population heterogeneity and differential susceptibility. This article reviews those developments and illustrates them with recent applications to environmentally relevant questions.

Implications of mechanism-based inhibition of CYP2D6 for the pharmacokinetics and toxicity of MDMA.

The aim of this study was to model the in vivo kinetic consequences of mechanism-based inhibition (MBI) of CYP2D6 by 3,4 methylenedioxymethamphetamine (MDMA, ecstasy). A model with physiologically-based components of drug metabolism was developed, taking account of change in the hepatic content of active CYP2D6 due to MBI by MDMA. Based on the in vitro information, plasma concentration time profiles of MDMA after various doses were computed and compared with reported observations. The analysis suggested that a typical recreational MDMA dose could inactivate most hepatic CYP2D6 within an hour, and the return to a basal level of CYP2D6 could take at least 10 days. Thus, the genetic polymorphism of CYP2D6 and coadministration of CYP2D6 inhibitors may have less impact on MDMA pharmacokinetics and the risk of acute toxicity than previously thought. This is consistent with clinical observations that indicate no obvious link between inherited CYP2D6 deficiency and acute MDMA intoxication.

Misuse of the well-stirred model of hepatic drug clearance

The “well-stirred” model of hepatic drug clearance was first proposed by Gillette ([1971][1]) and established by Rowland et al. ([1973][2]) and Wilkinson and Shand ([1975][3]). In the form that it is commonly used, net hepatic drug clearance based on whole-blood drug concentration (CLH,B) is

Variability in P-Glycoprotein Inhibitory Potency (IC50) Using Various in Vitro Experimental Systems: Implications for Universal Digoxin Drug-Drug Interaction Risk Assessment Decision Criteria

A P-glycoprotein (P-gp) IC50 working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC50 determinations. Each laboratory followed its in-house protocol to determine in vitro IC50 values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells—Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLC-PK1-MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC50 values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC50 values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC50 values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratio-based equation generally resulted in severalfold lower IC50 values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC50 values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC50 determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided.