Evaluation of Multiple in Vitro Systems for Assessment of CYP3A4 Induction in Drug Discovery: Human Hepatocytes, Pregnane X Receptor Reporter Gene, and Fa2N-4 and HepaRG Cells

McGinnity, Dermot F.; Zhang, George; Kenny, Jane R.; Hamilton, Geraldine A.; Otmani, Sara; Stams, Karen R.; Haney, Suzzette; Brassil, Patrick; Stresser, David M.; Riley, Robert J.

doi:10.1124/dmd.109.026526

Cited by 81 publications

(60 citation statements)

References 31 publications

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“…As previously stated in the literature, since similar predictive accuracy has been obtained with HepaRG cell line and human hepatocytes, data from both in vitro models can be used interchangeably within the same laboratory to predict in vivo clinical outcome for CYP3A4 induction (McGinnity et al, 2009). In terms of the accuracy in prediction of clinical outcome as shown by 2-fold error (%), our data also suggest comparable reliability of the two models (Tables 7 and 8).…”

Section: Discussionsupporting

confidence: 63%

Evaluation of Normalization Methods To Predict CYP3A4 Induction in Six Fully Characterized Cryopreserved Human Hepatocyte Preparations and HepaRG Cells

Vermet

Raoust

Ngo

et al. 2015

Drug Metabolism and Disposition

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Prediction of drug-drug interactions due to cytochrome P450 isoform 3A4 (CYP3A4) overexpression is important because this CYP isoform is involved in the metabolism of about 30% of clinically used drugs from almost all therapeutic categories. Therefore, it is mandatory to attempt to predict the potential of a new compound to induce CYP3A4. Among several in vitro-in vivo extrapolation methods recently proposed in the literature, an approach using a scaling factor, called a d factor, for a given hepatocyte batch to provide extrapolation between in vitro induction data and clinical outcome has been adopted by leading health authorities. We challenged the relevance of the calibration factor determined using a set of 15 well-known clinical CYP3A4 inducers or the potent CYP3A4 inducer rifampicin only. These investigations were conducted using six batches of human hepatocytes and an established HepaRG cell line. Our findings show that use of a calibration factor is preferable for clinical predictions, as shown previously by other investigators. Moreover, the present results also suggest that the accuracy of prediction through calculation of this factor is sufficient when rifampicin is considered alone, and the use of a larger set of fully characterized CYP3A4 clinical inducers is not required. For the established HepaRG cell line, the findings obtained in three experiments using a single batch of cells show a good prediction accuracy with or without the d factor. Additional investigations with different batches of HepaRG cell lines are needed to confirm these results.

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Section: Discussionsupporting

confidence: 63%

Evaluation of Normalization Methods To Predict CYP3A4 Induction in Six Fully Characterized Cryopreserved Human Hepatocyte Preparations and HepaRG Cells

Vermet

Raoust

Ngo

et al. 2015

Drug Metabolism and Disposition

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“…For carbamazepine the value of Ind slope used in Simcyp is 0.16. Static equations used E max and EC 50 values (7.7-fold and 40 M, respectively) from the literature (McGinnity et al, 2009). It is clear from Table 5 that predictions of AUC ratios from Simcyp and static equations are comparable.…”

Section: Evaluation Of Static and Dynamic Models For Ddi Predictionsmentioning

confidence: 94%

Evaluation of the Use of Static and Dynamic Models to Predict Drug-Drug Interaction and Its Associated Variability: Impact on Drug Discovery and Early Development

Peters¹,

Schroeder²,

Giri³

et al. 2012

Drug Metab Dispos

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ABSTRACT:Simcyp, a population-based simulator, is widely used for evaluating drug-drug interaction (DDI) risks in healthy and disease populations. We compare the prediction performance of Simcyp with that of mechanistic static models using different types of inhibitor concentrations, with the aim of understanding their strengths/ weaknesses and recommending the optimal use of tools in drug discovery/early development. The inclusion of an additional term in static equations to consider the contribution of hepatic first pass to DDIs (AUCR hfp ) has also been examined. A second objective was to assess Simcyp's estimation of variability associated with DDIs. The data set used for the analysis comprises 19 clinical interactions from 11 proprietary compounds. Except for gut interaction parameters, all other input data were identical for Simcyp and static models. Static equations using an unbound average steady-state systemic inhibitor concentration (I sys ) and a fixed fraction of gut extraction and neglecting gut extraction in the case of induction interactions performed better than Simcyp (84% compared with 58% of the interactions predicted within 2-fold). Differences in the prediction outcomes between the static and dynamic models are attributable to differences in first-pass contribution to DDI. The inclusion of AUCR hfp in static equations leads to systematic overprediction of interaction, suggesting a limited role for hepatic first pass in determining inhibition-based DDIs for our data set. Our analysis supports the use of static models when elimination routes of the victim compound and the role of gut extraction for the victim and/or inhibitor in humans are not well defined. A fixed variability of 40% of predicted mean area under the concentration-time curve ratio is recommended.

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“…Moreover, modulation of the concentration of DMSO during the differentiation process can result in expression of cytochrome P450 and transporters at levels similar to or greater than those in primary human hepatocytes in culture (Aninat et al, 2006;Lübberstedt et al, 2011). Since becoming available, HepaRG cells have been used successfully for assessment of cytochrome P450 induction (McGinnity et al, 2009;Anthérieu et al, 2010) and in toxicology studies (Dumont et al, 2010;Lübberstedt et al, 2011;McGill et al, 2011) and appear to have the potential for further understanding of the interplay between drug metabolism, cell metabolism, and liver function in preclinical toxicological studies for either known drugs and new chemical entities. Kanebratt and Andersson (2008) have demonstrated activities of several major drug-metabolizing cytochrome P450s in cultured HepaRG cells, which were of a magnitude similar to that in primary hepatocytes.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Cryopreserved HepaRG Cells with Cryopreserved Human Hepatocytes for Prediction of Clearance for 26 Drugs

Zanelli¹,

Caradonna²,

Hallifax³

et al. 2011

Drug Metab Dispos

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ABSTRACT:Prediction of clearance in drug discovery currently relies on human primary hepatocytes, which can vary widely in drug-metabolizing enzyme activity. Potential alternative in vitro models include the HepaRG cell (from immortalized hepatoma cells), which in culture can express drug-metabolizing enzymes to an extent comparable to that of primary hepatocytes. Utility of the HepaRG cell will depend on robust performance, relative to that of primary hepatocytes, in routine high-throughput analysis. In this study, we compared intrinsic clearance (CL int ) in the recently developed cryopreserved HepaRG cell system with CL int in human cryopreserved pooled hepatocytes and with CL int in vivo for 26 cytochrome P450 substrate drugs. There was quantitative agreement between CL int in HepaRG cells and human hepatocytes, which was linear throughout the range of CL int (1-2000 ml ⅐ min ؊1 ⅐ kg ؊1 ) and not dependent on particular cytochrome P450 involvement. Prediction of CL int in HepaRG cells was on average within 2-fold of in vivo CL int (using the well stirred liver model), but average fold error was clearance-dependent with greater underprediction (up to at least 5-fold) for the more highly cleared drugs. Recent reporting of this phenomenon in human hepatocytes was therefore confirmed with the hepatocytes used in this study, and hence the HepaRG cell system appears to share an apparently general tendency of clearance-limited CL int in cell models. This study shows the cryopreserved HepaRG cell system to be quantitatively comparable to human hepatocytes for prediction of clearance of drug cytochrome P450 substrates and to represent a promising alternative in vitro tool.

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Evaluation of Multiple in Vitro Systems for Assessment of CYP3A4 Induction in Drug Discovery: Human Hepatocytes, Pregnane X Receptor Reporter Gene, and Fa2N-4 and HepaRG Cells

Cited by 81 publications

References 31 publications

Evaluation of Normalization Methods To Predict CYP3A4 Induction in Six Fully Characterized Cryopreserved Human Hepatocyte Preparations and HepaRG Cells

Evaluation of Normalization Methods To Predict CYP3A4 Induction in Six Fully Characterized Cryopreserved Human Hepatocyte Preparations and HepaRG Cells

Evaluation of the Use of Static and Dynamic Models to Predict Drug-Drug Interaction and Its Associated Variability: Impact on Drug Discovery and Early Development

Comparison of Cryopreserved HepaRG Cells with Cryopreserved Human Hepatocytes for Prediction of Clearance for 26 Drugs

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