Application of PBPK modeling to predict human intestinal metabolism of CYP3A substrates – An evaluation and case study using GastroPlus™

F. Hoffmann-La Roche AG, pRED, Pharma Research & Early Development, Non-Clinical Safety, Basel, Switzerland.
European journal of pharmaceutical sciences: official journal of the European Federation for Pharmaceutical Sciences (Impact Factor: 3.35). 06/2012; 47(2):375-86. DOI: 10.1016/j.ejps.2012.06.013
Source: PubMed


First pass metabolism in the intestinal mucosa is a determinant of oral bioavailability of CYP3A substrates and so the prediction of intestinal availability (Fg) of potential drug candidates is important. Although intestinal metabolism can be modeled in commercial physiologically based pharmacokinetic (PBPK) software tools, a thorough evaluation of prediction performance is lacking. The current study evaluates the accuracy and precision of GastroPlus™ Fg predictions for 20 CYP3A substrates using in vitro and in silico input data for metabolic clearance and membrane permeation, and illustrates a potential impact of intestinal metabolism modeling on decision making in a drug Research and Development project.

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Available from: Neil Parrott, Apr 26, 2014
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    • "Absorption, distribution and excretion of compounds with poor passive membrane permeability is often significantly affected by active transport. PBPK modeling of such compounds has been limited by insufficient information on protein abundance and the lack of verified methods to translate in vitro measurements of transport to the in vivo situation [115] [116] [123]. This limits the predictive utility of the approach since in vivo data is needed to allow optimization of empirical scaling factors [17]. "
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    ABSTRACT: Pharmacokinetics (PK) refers to the time course of drug concentrations in the body and since knowledge of PK aids understanding of drug efficacy and safety, numerous PK studies are performed in animals and humans during the drug development process. In vitro to in vivo extrapolation (IVIVE) and physiologically-based pharmacokinetic (PBPK) modeling are tools that integrate data from various in silico, in vitro and in vivo sources to deliver mechanistic quantitative simulations of in vivo PK. PBPK models are used to predict human PK and to evaluate the effects of intrinsic factors such as organ dysfunction, age and genetics as well as extrinsic factors such as co-administered drugs. In recent years the use of PBPK within the industry has greatly increased. However insufficient data on how the abundance of metabolic enzymes and membrane transporters vary in different human patient populations and in different species has been a limitation. A major advance is therefore expected through reliable quantification of the abundance of these proteins in tissues. This review describes the role of PBPK modelling in drug discovery and development, outlines the assumptions involved in integrating protein abundance data, and describes the advances made and expected in determining abundance of relevant proteins through mass spectrometric techniques. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
    PROTEOMICS - CLINICAL APPLICATIONS 02/2015; 9(7-8). DOI:10.1002/prca.201400147 · 2.96 Impact Factor
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    • "In this case, parameters affecting rate and extent of absorption were solubility, permeability, particle size, intestinal transit times and gastric emptying time. As the most sensitive parameter, permeability was selected to adjust the intestinal absorption model whereas other parameters were kept at default values (Heikkinen et al., 2012). The multiplicative P eff factor was used to modulate P eff in order to fit the absorption phase for the simulated profile and obtain C max and T max values to within 30% of the observed values. "
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    ABSTRACT: The induction of cytochrome P450 enzymes (CYPs) is an important source of drug-drug interaction (DDI) and can result in pronounced changes in pharmacokinetics (PK). Rifampicin (RIF) is a potent inducer of CYP3A4 and also acts as a competitive inhibitor which can partially mask the induction. The objective of this study was to determine a clinical DDI study design for RIF resulting in maximum CYP3A4 induction. A physiologically based pharmacokinetic (PBPK) model was developed to project the dynamics and magnitude of CYP3A4 induction in vivo from in vitro data generated with primary human hepatocytes. The interaction model included both inductive and inhibitory effects of RIF on CYP3A4 in gut and liver and accounting for the observed RIF auto-induction. The model has been verified for 4 CYP3A4 substrates: midazolam, triazolam, alfentanil and nifedipine using plasma concentration data from 20 clinical study designs with intravenous (n=7) and oral (n=13) administrations. Finally, the influence of the time between RIF and substrate administration was explored for the interaction between midazolam and RIF. The model integrating in vitro induction parameters correctly predicted intravenous induction but underestimated oral induction with 30% of simulated concentrations more than 2 fold higher than of observed data. The use of a 1.6 fold higher value for the maximum induction effect (Emax) improved significantly the accuracy and precision of oral induction with 82% of simulated concentrations and all predicted PK parameters within 2 fold of observed data. Our simulations suggested that a concomitant administration of RIF and midazolam resulted in significant competitive inhibition limited to intestinal enzyme. Accordingly, a maximum induction effect could be achieved with a RIF pretreatment of 600 mg/day during 5 days and a substrate administration at least 2 h after the last RIF dose. A period of 2 weeks after RIF removal was found sufficient to allow return to baseline levels of enzyme.
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    ABSTRACT: The objective of this study was to evaluate the impact of interindividual differences in hepatic first-pass effect (FPE) on the magnitude of the human kinetic adjustment factor (HKAF) for ingested toxicants. This factor aims at replacing a default value of 3.2 used in non-cancer risk assessment. Coupled with Monte Carlo simulations, steady-state equations that account for FPE were used to obtain distributions of arterial blood concentrations (CAss) and rates of metabolism in adults, neonates, infants and toddlers continuously exposed to an oral dose of 1 μg/kg/d of theoretical CYP2E1 and CYP1A2 substrates. For such substrates exhibiting a range of blood:air partition coefficients (Pb: 1-10,000) and hepatic extraction ratios in an average adult (E(ad): 0.01-0.99), HKAFs were computed as the ratio of the 95(th) percentile of dose metrics for each subpopulation over the 50(th) percentile value in adults. The reduced hepatic enzyme content in neonates as compared to adults resulted in correspondingly diminished FPE. Consequently, HKAFs greater than 3.2 could be observed, based on CAss only, in the following cases: for some CYP2E1 substrates with E(ad) ⩽ 0.3, in neonates (max.: 6.3); and for some CYP1A2 substrates with E(ad) ⩽ 0.1 and 0.7, in respectively neonates and infants (max.: 28.3). Overall, this study pointed out the importance of accounting for child/adult differences in FPE when determining the HKAF for oral exposure.
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