Skip to main content
Log in

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

  • Original Research Article
  • Published:
Clinical Pharmacokinetics Aims and scope Submit manuscript

Abstract

Background

Apalutamide is predominantly metabolized via cytochrome P450 (CYP) 2C8 and CYP3A4, whose contributions change due to autoinduction with repeated dosing.

Objectives

We aimed to predict CYP3A4 and CYP2C8 inhibitor/inducer effects on the steady-state pharmacokinetics of apalutamide and total potency-adjusted pharmacologically active moieties, and simulated drug–drug interaction (DDI) between single-dose and repeated-dose apalutamide coadministered with known inhibitors/inducers.

Methods

We applied physiologically based pharmacokinetic modeling for our predictions, and simulated DDI between single-dose and repeated-dose apalutamide 240 mg coadministered with ketoconazole, gemfibrozil, or rifampicin.

Results

The estimated contribution of CYP2C8 and CYP3A4 to apalutamide metabolism is 58% and 13%, respectively, after single dosing, and 40% and 37%, respectively, at steady-state. Apalutamide exposure is predicted to increase with ketoconazole (maximum observed concentration at steady-state [Cmax,ss] 38%, area under the plasma concentration–time curve at steady-state [AUCss] 51% [pharmacologically active moieties, Cmax,ss 23%, AUCss 28%]) and gemfibrozil (Cmax,ss 32%, AUCss 44% [pharmacologically active moieties, Cmax,ss 19%, AUCss 23%]). Rifampicin exposure is predicted to decrease apalutamide (Cmax,ss 25%, AUCss 34% [pharmacologically active moieties, Cmax,ss 15%, AUCss 19%]).

Conclusions

Based on our simulations, no major changes in the pharmacokinetics of apalutamide or pharmacologically active moieties are expected with strong CYP3A4/CYP2C8 inhibitors/inducers. This observation supports the existing recommendations that no dose adjustments are needed during coadministration of apalutamide and the known inhibitors or inducers of CYP2C8 or CYP3A4.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data Availability

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Clegg NJ, Wongvipat J, Joseph JD, et al. ARN-509: a novel antiandrogen for prostate cancer treatment. Cancer Res. 2012;72(6):1494–503.

    Article  CAS  Google Scholar 

  2. ERLEADA (apalutamide) [prescribing information]. Horsham, PA: Janssen Pharmaceutical Companies; 2019.

  3. ERLEADA [summary of product characteristics]. The electronic Medicines Compendium (eMC). Available at: https://www.ema.europa.eu/en/documents/product-information/erleada-epar-product-information_en.pdf. Accessed 4 Oct 2019.

  4. Rathkopf D, Scher HI. Androgen receptor antagonists in castration-resistant prostate cancer. Cancer J. 2013;19(1):43–9.

    Article  CAS  Google Scholar 

  5. Smith MR, Saad F, Chowdhury S, et al. Apalutamide treatment and metastasis-free survival in prostate cancer. N Engl J Med. 2018;378(15):1408–18.

    Article  CAS  Google Scholar 

  6. Chi KN, Agarwal N, Bjartell A, et al. Apalutamide for metastatic, castration-sensitive prostate cancer. N Engl J Med. 2019;381(1):13–24.

    Article  CAS  Google Scholar 

  7. Smith MR, Rathkopf DE, Mulders PF, et al. Efficacy and safety of abiraterone acetate in elderly (75 years or older) chemotherapy naive patients with metastatic castration resistant prostate cancer. J Urol. 2015;194(5):1277–84.

    Article  CAS  Google Scholar 

  8. Jamani R, Lee EK, Berry SR, et al. High prevalence of potential drug-drug interactions in patients with castration-resistant prostate cancer treated with abiraterone acetate. Eur J Clin Pharmacol. 2016;72(11):1391–9.

    Article  CAS  Google Scholar 

  9. Bonnet C, Boudou-Rouquette P, Azoulay-Rutman E, et al. Potential drug-drug interactions with abiraterone in metastatic castration-resistant prostate cancer patients: a prevalence study in France. Cancer Chemother Pharmacol. 2017;79(5):1051–5.

    Article  CAS  Google Scholar 

  10. Mittal BTS, Kumar S, Mittal RD, Agarwal G. Cytochrome P450 in cancer susceptibility and treatment. Adv Clin Chem. 2015;71:77–139.

    Article  CAS  Google Scholar 

  11. Cabrera MA, Dip RM, Furlan MO, Rodrigues SL. Use of drugs that act on the cytochrome P450 system in the elderly. Clinics (Sao Paulo). 2009;64(4):273–8.

    Article  Google Scholar 

  12. Ohno Y, Hisaka A, Suzuki H. General framework for the quantitative prediction of CYP3A4-mediated oral drug interactions based on the AUC increase by coadministration of standard drugs. Clin Pharmacokinet. 2007;46(8):681–96.

    Article  CAS  Google Scholar 

  13. LOPID (gemfibrozil) [prescribing information]. New York, NY: Parke-Davis, Division of Pfizer Inc.; 2008.

  14. PLAVIX (clopidogrel) [prescribing information]. Bridgewater, NJ: Bristol-Myers Squibb/Sanofi Pharmaceuticals; 2018.

  15. Spina E, Pisani F, Perucca E. Clinically significant pharmacokinetic drug interactions with carbamazepine. An update. Clin Pharmacokinet. 1996;31(3):198–214.

    Article  CAS  Google Scholar 

  16. Niemi M, Backman JT, Fromm MF, Neuvonen PJ, Kivisto KT. Pharmacokinetic interactions with rifampicin: clinical relevance. Clin Pharmacokinet. 2003;42(9):819–50.

    Article  CAS  Google Scholar 

  17. De Vries RJF, Mannens G, Snoeys J, Cuyckens F, Chien C, Ward P. Apalutamide absorption, metabolism, and excretion in healthy men, and enzyme reaction in human hepatocytes. Drug Metab Dispos. 2019;47(5):453–64.

    Article  Google Scholar 

  18. Rathkopf DE, Morris MJ, Fox JJ, et al. Phase I study of ARN-509, a novel antiandrogen, in the treatment of castration-resistant prostate cancer. J Clin Oncol. 2013;31(28):3525–30.

    Article  CAS  Google Scholar 

  19. Jones H, Rowland-Yeo K. Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development. CPT Pharmacometr Syst Pharmacol. 2013;2:e63.

    Article  Google Scholar 

  20. Min JS, Bae SK. Prediction of drug-drug interaction potential using physiologically based pharmacokinetic modeling. Arch Pharm Res. 2017;40(12):1356–79.

    Article  CAS  Google Scholar 

  21. Pang KS, Durk MR. Physiologically-based pharmacokinetic modeling for absorption, transport, metabolism and excretion. J Pharmacokinet Pharmacodyn. 2010;37(6):591–615.

    Article  CAS  Google Scholar 

  22. Shebley M, Sandhu P, Emami Riedmaier A, et al. Physiologically based pharmacokinetic model qualification and reporting procedures for regulatory submissions: a consortium perspective. Clin Pharmacol Ther. 2018;104(1):88–110.

    Article  Google Scholar 

  23. Zhao P, Zhang L, Grillo JA, et al. Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review. Clin Pharmacol Ther. 2011;89(2):259–67.

    Article  CAS  Google Scholar 

  24. Leibowitz-Amit R, Joshua AM. Targeting the androgen receptor in the management of castration-resistant prostate cancer: rationale, progress, and future directions. Curr Oncol. 2012;19(Suppl 3):S22–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Keizman D, Huang P, Carducci MA, Eisenberger MA. Contemporary experience with ketoconazole in patients with metastatic castration-resistant prostate cancer: clinical factors associated with PSA response and disease progression. Prostate. 2012;72(4):461–7.

    Article  CAS  Google Scholar 

  26. Doble N, Shaw R, Rowland-Hill C, Lush M, Warnock DW, Keal EE. Pharmacokinetic study of the interaction between rifampicin and ketoconazole. J Antimicrob Chemother. 1988;21(5):633–5.

    Article  CAS  Google Scholar 

  27. Ihunnah CA, Jiang M, Xie W. Nuclear receptor PXR, transcriptional circuits and metabolic relevance. Biochim Biophys Acta. 2011;1812(8):956–63.

    Article  CAS  Google Scholar 

  28. Baneyx G, Parrott N, Meille C, Iliadis A, Lave T. Physiologically based pharmacokinetic modeling of CYP3A4 induction by rifampicin in human: influence of time between substrate and inducer administration. Eur J Pharm Sci. 2014;56:1–15.

    Article  CAS  Google Scholar 

  29. Loos U, Musch E, Jensen JC, Mikus G, Schwabe HK, Eichelbaum M. Pharmacokinetics of oral and intravenous rifampicin during chronic administration. Klin Wochenschr. 1985;63(23):1205–11.

    Article  CAS  Google Scholar 

  30. Chen Y, Ma F, Lu T, et al. Development of a physiologically based pharmacokinetic model for itraconazole pharmacokinetics and drug-drug interaction prediction. Clin Pharmacokinet. 2016;55(6):735–49.

    Article  CAS  Google Scholar 

  31. Han B, Mao J, Chien JY, Hall SD. Optimization of drug-drug interaction study design: comparison of minimal physiologically based pharmacokinetic models on prediction of CYP3A inhibition by ketoconazole. Drug Metab Dispos. 2013;41(7):1329–38.

    Article  CAS  Google Scholar 

  32. Varma MV, Lin J, Bi YA, Kimoto E, Rodrigues AD. Quantitative rationalization of gemfibrozil drug interactions: consideration of transporters-enzyme interplay and the role of circulating metabolite gemfibrozil 1-O-beta-glucuronide. Drug Metab Dispos. 2015;43(7):1108–18.

    Article  CAS  Google Scholar 

  33. Chiba K, Shimizu K, Kato M, et al. Prediction of inter-individual variability in the pharmacokinetics of CYP2C19 substrates in humans. Drug Metab Pharmacokinet. 2014;29(5):379–86.

    Article  Google Scholar 

  34. Seidegard J, Nyberg L, Borga O. Differentiating mucosal and hepatic metabolism of budesonide by local pretreatment with increasing doses of ketoconazole in the proximal jejunum. Eur J Pharm Sci. 2012;46(5):530–6.

    Article  Google Scholar 

  35. de Zwart L, Snoeys J, De Jong J, Sukbuntherng J, Mannaert E, Monshouwer M. Ibrutinib dosing strategies based on interaction potential of CYP3A4 perpetrators using physiologically based pharmacokinetic modeling. Clin Pharmacol Ther. 2016;100(5):548–57.

    Article  Google Scholar 

  36. Narayanan RHM, Kumar G, Surapaneni S. Application of a “fit for purpose” PBPK model to investigate the CYP3A4 induction potential of enzalutamide. Drug Metab Lett. 2016;10(3):172–9.

    Article  CAS  Google Scholar 

  37. Snoeys J, Beumont M, Monshouwer M, Ouwerkerk-Mahadevan S. Mechanistic understanding of the nonlinear pharmacokinetics and intersubject variability of simeprevir: a PBPK-guided drug development approach. Clin Pharmacol Ther. 2016;99(2):224–34.

    Article  CAS  Google Scholar 

  38. Jaruratanasirikul S, Sriwiriyajan S. Effect of rifampicin on the pharmacokinetics of itraconazole in normal volunteers and AIDS patients. Eur J Clin Pharmacol. 1998;54(2):155–8.

    Article  CAS  Google Scholar 

  39. Honkalammi J, Niemi M, Neuvonen PJ, Backman JT. Gemfibrozil is a strong inactivator of CYP2C8 in very small multiple doses. Clin Pharmacol Ther. 2012;91(5):846–55.

    Article  CAS  Google Scholar 

  40. Tornio A, Filppula AM, Kailari O, et al. Glucuronidation converts clopidogrel to a strong time-dependent inhibitor of CYP2C8: a phase II metabolite as a perpetrator of drug-drug interactions. Clin Pharmacol Ther. 2014;96(4):498–507.

    Article  CAS  Google Scholar 

  41. Smith MR, Perez-Ruixo C, Ackaert O, et al. Relationship between apalutamide (APA) exposure and metastasis-free survival (MFS) in patients (pts) with nonmetastatic castration-resistant prostate cancer (nmCRPC) from SPARTAN [abstract]. Ann Oncol. 2018;29(Suppl 8):viii278. https://doi.org/10.1093/annonc/mdy284.015.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank William Turner, PhD, and Ira Mills, PhD, employees of Parexel, for medical writing assistance, which was funded by Janssen Global Services, LLC. “Pharmacokinetic Drug–Drug Interaction of Apalutamide, Part 1: Clinical Studies in Healthy Men and Patients with Castration-Resistant Prostate Cancer” has also been published in Clinical Pharmacokinetics as a companion manuscript.

Author information

Authors and Affiliations

Authors

Contributions

Writing (original draft preparation): AVdB, JS, LDZ, PW, AL-G, DO, MM, and CC. Writing (review and editing): AVdB, JS, LDZ, PW, AL-G, DO, MM, and CC. Research design: AVdB, JS, LDZ, PW, MM, and CC. Performing the research: AVdB and JS. Data analysis: AVdB and JS.

Corresponding author

Correspondence to An Van den Bergh.

Ethics declarations

Funding

This study was funded by Janssen Research & Development. Editorial assistance was provided by William Turner, PhD, and Ira Mills, PhD, of Parexel, with funding from Janssen Global Services, LLC.

Conflicts of Interest

An Van den Bergh, Jan Snoeys, Loeckie De Zwart, Peter Ward, Angela Lopez-Gitlitz, Daniele Ouellet, Mario Monshouwer, and Caly Chien are current or former employees of Janssen Research & Development and hold/held stock in Johnson & Johnson.

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

Informed Consent

As this was a modeling and simulation study that did not include human subjects, informed consent was not required.

Additional information

Daniele Ouellet and Caly Chien were employees of Janssen Research & Development during the conduct of the study, analysis, and interpretation of the results.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 782 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Van den Bergh, A., Snoeys, J., De Zwart, L. et al. Pharmacokinetic Drug–Drug Interaction of Apalutamide, Part 2: Investigating Interaction Potential Using a Physiologically Based Pharmacokinetic Model. Clin Pharmacokinet 59, 1149–1160 (2020). https://doi.org/10.1007/s40262-020-00881-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40262-020-00881-3

Navigation