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Physiologically based pharmacokinetic modeling of ponatinib to describe drug–drug interactions in patients with cancer

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Abstract

Purpose

This study aimed to investigate the drug–drug interactions of ponatinib with strong, moderate, or weak CYP3A4 inhibitors/inducers by developing physiologically based pharmacokinetic (PBPK) models.

Methods

Simcyp® Ver 20.1 (Certara Inc., Sheffield, UK) was used to construct a PBPK model for ponatinib and to predict its interaction with strong, moderate, or weak CYP3A4 inhibitors/inducers. The constructed model was validated by comparing predicted values with actual observed values. Inhibitors or inducers that increased or decreased the area under the plasma concentration curve of ponatinib by more than two-fold when used in combination were considered significant.

Results

The PBPK model of ponatinib accurately represented its oral pharmacokinetics. It also reasonably predicted its pharmacokinetics when combined with ketoconazole and rifampicin. No weak to strong CYP3A4 inhibitor combinations significantly increased the AUC of ponatinib. However, the strong CYP3A4 inducers rifampicin (oral, 600 mg QD) and phenytoin (oral, 100 mg TID) decreased AUC by 60–70% and 50%, respectively.

Conclusions

The PBPK model predicted a significant drug interaction when ponatinib was combined with a strong CYP3A4 inducer. Conversely, the combination with weak-to-strong CYP3A4 inhibitors did not suggest a drug interaction with ponatinib.

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References

  1. O’Hare T, Shakespeare WC, Zhu X et al (2009) AP24534, a pan-BCR-ABL inhibitor for chronic myeloid leukemia, potently inhibits the T315I mutant and overcomes mutation-based resistance. Cancer Cell 16(5):401–412

    Article  Google Scholar 

  2. Deininger MW, Hodgson JG, Shah NP et al (2016) Compound mutations in BCR-ABL1 are not major drivers of primary or secondary resistance to ponatinib in CP-CML patients. Blood 127(6):703–712

    Article  CAS  Google Scholar 

  3. Baccarani M, Deininger MW, Rosti G et al (2013) European leukemia net recommendations for the management of chronic myeloid leukemia: 2013. Blood 122(6):872–884

    Article  CAS  Google Scholar 

  4. Clinical Pharmacology and Biopharmaceutics Review(s): Iclusig®(ponatinib tablets). Pharmaceuticals and Medical Devices Agency in Japan. https://www.pmda.go.jp/drugs/2016/P20161021002/index.html

  5. Narasimhan NI, Dorer DJ, Davis J et al (2014) Evaluation of pharmacokinetics and safety of ponatinib in subjects with chronic hepatic impairment and matched healthy subjects. Cancer Chemother Pharmacol 74:341–348

    Article  CAS  Google Scholar 

  6. Narasimhan NI, Dorer DJ, Niland K et al (2013) Effects of ketoconazole on the pharmacokinetics of ponatinib in healthy subjects. J Clin Pharmacol 53(9):974–981

    Article  CAS  Google Scholar 

  7. Narasimhan NI, Dorer DJ, Davis J et al (2015) Evaluation of the effect of multiple doses of rifampin on the pharmacokinetics and safety of ponatinib in healthy subjects. Clin Pharmacol Drug Dev 4(5):354–360

    Article  CAS  Google Scholar 

  8. Tojo A, Kyo T, Yamamoto K, Nakamae H et al (2017) Ponatinib in Japanese patients with Philadelphia chromosome-positive leukemia, a phase 1/2 study. Int J Hematol 106:385–397

    Article  CAS  Google Scholar 

  9. Dorer DJ, Knickerbocker RK, Baccarani M et al (2016) Impact of dose intensity of ponatinib on selected adverse events: Multivariate analyses from a pooled population of clinical trial patients. Leuk Res 48:84–91

    Article  CAS  Google Scholar 

  10. Larson RA (2018) Managing CNS disease in adults with acute lymphoblastic leukemia. Leuk Lymphoma 59:3–13

    Article  CAS  Google Scholar 

  11. Assessment report: Iclusig®(ponatinib tablets). European Medicines Agency. https://www.ema.europa.eu/en/documents/assessment-report/iclusig-epar-public-assessment-report_en.pdf.

  12. Ye YE, Woodward CN, Narasimhan NI (2017) Absorption, metabolism, and excretion of [14 C] ponatinib after a single oral dose in humans. Cancer Chemother Pharmacol 79(3):507–518

    Article  CAS  Google Scholar 

  13. Ono C, Hsyu PH, Abbas R et al (2017) Application of physiologically based pharmacokinetic modeling for the understanding of bosutinib pharmacokinetics: prediction of drug–drug and drug-disease interactions. Drug Metab Dispos 45(4):390–398

    Article  CAS  Google Scholar 

  14. Rowland Yeo K, Jamei M, Yang J, A. et al (2010) 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. Eur J Pharm Sci. 39:298–309

    Article  CAS  Google Scholar 

  15. Friedman EJ, Fraser IP, Wang YH et al (2011) Effect of different durations and formulations of diltiazem on the single-dose pharmacokinetics of midazolam: how long do we go? J Clin Pharmacol 51:1561–1570

    Article  CAS  Google Scholar 

  16. Zhang X, Quinney SK, Gorski JC et al (2009) Semiphysiologically based pharmacokinetic models for the inhibition of midazolam clearance by diltiazem and its major metabolite. Drug Metab Dispos 37:1587–1597

    Article  CAS  Google Scholar 

  17. Li X, Junge L, Taubert M, von Georg A et al (2020) A novel study design using continuous intravenous and intraduodenal infusions of midazolam and voriconazole for mechanistic quantitative assessment of hepatic and intestinal CYP3A inhibition. J Clin Pharmacol 60:1237–1253

    Article  CAS  Google Scholar 

  18. Lee S, Kim BH, Nam WS et al (2012) Effect of CYP2C19 polymorphism on the pharmacokinetics of voriconazole after single and multiple doses in healthy volunteers. J Clin Pharmacol 52:195–203

    Article  CAS  Google Scholar 

  19. Drug Development and Drug Interactions: U.S. Food and Drug Administration. https://www.fda.gov/drugs/drug-interactions-labeling/drug-development-and-drug-interactions-table-substrates-inhibitors-and-inducers

  20. Hanley MJ, Diderichsen PM, Narasimhan N et al (2021) Population pharmacokinetics of ponatinib in healthy adult volunteers and patients with hematologic malignancies and model-informed dose selection for pediatric development. J Clin Pharmacol. 62(4):555–567

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by the Foundation of Cancer Research in Japan.

Funding

The Foundation for the Promotion of Cancer Research in Japan supported this study (Grant number: FPCR-2022-B).

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Authors and Affiliations

  1. Department of Pharmacometrics and Pharmacokinetics, Meiji Pharmaceutical University, 2-522-1 Nojio, Kiyose, Tokyo, Japan

    Tomoko O. Morita & Kazuhiko Hanada

  2. Department of Clinical Research Support, National Cancer Hospital, Tokyo, Japan

    Tomoko O. Morita

Authors
  1. Tomoko O. Morita
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  2. Kazuhiko Hanada
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Contributions

TOM: study planning, conducting research, data analysis. KH: study planning.

Corresponding author

Correspondence to Tomoko O. Morita.

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The authors declare no competing interests.

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Each patient provided written informed consent to participate.

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Morita, T.O., Hanada, K. Physiologically based pharmacokinetic modeling of ponatinib to describe drug–drug interactions in patients with cancer. Cancer Chemother Pharmacol 90, 315–323 (2022). https://doi.org/10.1007/s00280-022-04466-8

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  • DOI: https://doi.org/10.1007/s00280-022-04466-8

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