Literature DB >> 34495458

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

Nassim Djebli1, Vincent Buchheit2, Neil Parrott2, Elena Guerini2, Yumi Cleary2, Stephen Fowler2, Nicolas Frey2, Li Yu3, François Mercier2, Alex Phipps4, Georgina Meneses-Lorente4.   

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.
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

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Year:  2021        PMID: 34495458     DOI: 10.1007/s13318-021-00714-z

Source DB:  PubMed          Journal:  Eur J Drug Metab Pharmacokinet        ISSN: 0378-7966            Impact factor:   2.441


  10 in total

Review 1.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Authors:  Jennifer E Sager; Jingjing Yu; Isabelle Ragueneau-Majlessi; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2015-08-21       Impact factor: 3.922

2.  Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions.

Authors:  Trudy Rodgers; Malcolm Rowland
Journal:  J Pharm Sci       Date:  2006-06       Impact factor: 3.534

3.  Safety and Antitumor Activity of the Multitargeted Pan-TRK, ROS1, and ALK Inhibitor Entrectinib: Combined Results from Two Phase I Trials (ALKA-372-001 and STARTRK-1).

Authors:  Alexander Drilon; Salvatore Siena; Sai-Hong Ignatius Ou; Manish Patel; Myung Ju Ahn; Jeeyun Lee; Todd M Bauer; Anna F Farago; Jennifer J Wheler; Stephen V Liu; Robert Doebele; Laura Giannetta; Giulio Cerea; Giovanna Marrapese; Michele Schirru; Alessio Amatu; Katia Bencardino; Laura Palmeri; Andrea Sartore-Bianchi; Angelo Vanzulli; Sara Cresta; Silvia Damian; Matteo Duca; Elena Ardini; Gang Li; Jason Christiansen; Karey Kowalski; Ann D Johnson; Rupal Patel; David Luo; Edna Chow-Maneval; Zachary Hornby; Pratik S Multani; Alice T Shaw; Filippo G De Braud
Journal:  Cancer Discov       Date:  2017-02-09       Impact factor: 39.397

4.  Physiologically Based Absorption Modelling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Entrectinib.

Authors:  Neil Parrott; Cordula Stillhart; Marc Lindenberg; Bjoern Wagner; Karey Kowalski; Elena Guerini; Nassim Djebli; Georgina Meneses-Lorente
Journal:  AAPS J       Date:  2020-05-26       Impact factor: 4.009

Review 5.  Population-based mechanistic prediction of oral drug absorption.

Authors:  Masoud Jamei; David Turner; Jiansong Yang; Sibylle Neuhoff; Sebastian Polak; Amin Rostami-Hodjegan; Geoffrey Tucker
Journal:  AAPS J       Date:  2009-04-21       Impact factor: 4.009

6.  Pharmacokinetic Drug-Drug Interaction of Apalutamide, Part 2: Investigating Interaction Potential Using a Physiologically Based Pharmacokinetic Model.

Authors:  An Van den Bergh; Jan Snoeys; Loeckie De Zwart; Peter Ward; Angela Lopez-Gitlitz; Daniele Ouellet; Mario Monshouwer; Caly Chien
Journal:  Clin Pharmacokinet       Date:  2020-09       Impact factor: 6.447

Review 7.  A framework for assessing inter-individual variability in pharmacokinetics using virtual human populations and integrating general knowledge of physical chemistry, biology, anatomy, physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition of covariates.

Authors:  Masoud Jamei; Gemma L Dickinson; Amin Rostami-Hodjegan
Journal:  Drug Metab Pharmacokinet       Date:  2009       Impact factor: 3.614

8.  In vitro and clinical investigations to determine the drug-drug interaction potential of entrectinib, a small molecule inhibitor of neurotrophic tyrosine receptor kinase (NTRK).

Authors:  Georgina Meneses-Lorente; Stephen Fowler; Elena Guerini; Karey Kowalski; Edna Chow-Maneval; Li Yu; Francois Mercier; Mohammed Ullah; Kenichi Umehara; Andreas Brink; Vincent Buchheit; Elke Zwanziger; Alex Phipps; Nassim Djebli
Journal:  Invest New Drugs       Date:  2021-08-21       Impact factor: 3.850

9.  Predicting Clinical Effects of CYP3A4 Modulators on Abemaciclib and Active Metabolites Exposure Using Physiologically Based Pharmacokinetic Modeling.

Authors:  Maria M Posada; Bridget L Morse; P Kellie Turner; Palaniappan Kulanthaivel; Stephen D Hall; Gemma L Dickinson
Journal:  J Clin Pharmacol       Date:  2020-02-20       Impact factor: 3.126

Review 10.  Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations.

Authors:  Kunal S Taskar; Venkatesh Pilla Reddy; Howard Burt; Maria M Posada; Manthena Varma; Ming Zheng; Mohammed Ullah; Arian Emami Riedmaier; Ken-Ichi Umehara; Jan Snoeys; Masanori Nakakariya; Xiaoyan Chu; Maud Beneton; Yuan Chen; Felix Huth; Rangaraj Narayanan; Dwaipayan Mukherjee; Vaishali Dixit; Yuichi Sugiyama; Sibylle Neuhoff
Journal:  Clin Pharmacol Ther       Date:  2019-12-31       Impact factor: 6.875

  10 in total
  1 in total

1.  Entrectinib in children and young adults with solid or primary CNS tumors harboring NTRK, ROS1, or ALK aberrations (STARTRK-NG).

Authors:  Ami V Desai; Giles W Robinson; Karen Gauvain; Ellen M Basu; Margaret E Macy; Luke Maese; Nicholas S Whipple; Amit J Sabnis; Jennifer H Foster; Suzanne Shusterman; Janet Yoon; Brian D Weiss; Mohamed S Abdelbaki; Amy E Armstrong; Thomas Cash; Christine A Pratilas; Nadège Corradini; Lynley V Marshall; Mufiza Farid-Kapadia; Saibah Chohan; Clare Devlin; Georgina Meneses-Lorente; Alison Cardenas; Katherine E Hutchinson; Guillaume Bergthold; Hubert Caron; Edna Chow Maneval; Amar Gajjar; Elizabeth Fox
Journal:  Neuro Oncol       Date:  2022-10-03       Impact factor: 13.029

  1 in total

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