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Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making

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European Journal of Drug Metabolism and Pharmacokinetics Aims and scope Submit manuscript

Abstract

Background and Objective

Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers.

Methods

A PBPK model was established in Simcyp® Simulator. The initial model based on in vitro–in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug–drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics.

Results

The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%.

Conclusions

The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.

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Acknowledgements

The clinical studies reported in this manuscript were funded by F. Hoffmann-La-Roche (formerly Ignyta Inc., a member of the Roche Group). The modeling analyses were also funded by F. Hoffmann-La-Roche.

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Authors and Affiliations

  1. Roche Pharmaceutical Research and Early Development, Roche Innovation Center, F. Hoffmann-La Roche Ltd, Basel, Switzerland

    Nassim Djebli, Vincent Buchheit, Neil Parrott, Elena Guerini, Yumi Cleary, Stephen Fowler, Nicolas Frey & François Mercier

  2. Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Jersey City, NJ, USA

    Li Yu

  3. Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Roche Products Ltd, Welwyn, UK

    Alex Phipps & Georgina Meneses-Lorente

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  1. Nassim Djebli
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Corresponding author

Correspondence to Nassim Djebli.

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Funding

The clinical studies reported in this manuscript were funded by F. Hoffmann-La-Roche (formerly Ignyta Inc., a member of the Roche Group). The modeling analyses were also funded by F. Hoffmann-La-Roche. Administrative support was provided by Ashfield Medcomms, an Ashfield Health company, and was funded by F. Hoffmann-La Roche Ltd.

Conflicts of Interest

G.M-L. is an employee of Roche Products Ltd. N.D. E.G. Y.C., and A.P. are employees and stockholders of F. Hoffmann-La Roche Ltd. F.M., V.B., N.P., N.F., and S.F. are employees of Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. L.Y. is a former employee of the Roche Innovation Center, Little Falls, NJ, USA.

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Qualified researchers may request access to individual patient level data through the clinical study data request platform (https://vivli.org/). Further details on Roche's criteria for eligible studies are available here (https://vivli.org/members/ourmembers/). For further details on Roche's Global Policy on the Sharing of Clinical Information and how to request access to related clinical study documents, see here (https://www.roche.com/research_and_development/who_we_are_how_we_work/clinical_trials/our_commitment_to_data_sharing.htm).

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Authors' Contributions

All authors were involved in interpretation of the data, revising the manuscript critically for important intellectual content, approved the final version, and agree to be accountable for the work. Additionally, the authors contributed as follows: S.F. performed the data analysis; V.B. contributed to the conception and planning of the work that led to the manuscript; N.B. drafted the manuscript content.

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All studies were approved by the relevant ethics committees, and were conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice guidelines.

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All subjects provided written informed consent prior to enrollment in the clinical studies.

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Djebli, N., Buchheit, V., Parrott, N. et al. Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making. Eur J Drug Metab Pharmacokinet 46, 779–791 (2021). https://doi.org/10.1007/s13318-021-00714-z

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