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Clinical Pharmacokinetics

, Volume 58, Issue 5, pp 615–625 | Cite as

Bridging Olaparib Capsule and Tablet Formulations Using Population Pharmacokinetic Meta-analysis in Oncology Patients

  • Diansong Zhou
  • Jianguo Li
  • Khanh Bui
  • Maria Learoyd
  • Alienor Berges
  • Tsveta Milenkova
  • Nidal Al-Huniti
  • Helen Tomkinson
  • Hongmei XuEmail author
Original Research Article

Abstract

Background

Olaparib is a first-in-class potent oral poly(ADP-ribose) polymerase inhibitor.

Objectives

The aims of this analysis were to establish an integrated population pharmacokinetic (PK) model of olaparib in patients with solid tumors and to bridge the PK of olaparib between capsule and tablet formulations.

Methods

The population PK model was developed using plasma concentration data from 659 patients in 11 phase I, II, and III studies of olaparib tablets/capsules monotherapy. Relative bioavailability between the tablet and capsule formulations was estimated and the relative exposure between olaparib tablet and capsule therapeutic doses was further assessed.

Results

The concentration–time profile was described using a two-compartment model with sequential zero- and first-order absorption and first-order elimination for both capsules and tablets with different absorption parameters. Multiple-dose clearance compared with single-dose clearance was reduced by approximately 15% (auto-inhibition). Disease severity had an impact on olaparib clearance, and tablet strength had an impact on Ka. The olaparib geometric mean area under the curve (AUC) and maximal concentration (Cmax) following a single 300 mg tablet were 42.1 μg h/mL and 5.8 μg/mL, respectively, and the steady-state geometric mean AUC and Cmax following a 300 mg tablet twice daily were 49.0 μg h/mL and 7.7 μg/mL, respectively. The relative exposure (AUC) of the 300 mg tablet formulation is 13% higher than the 400 mg capsule formulation.

Conclusion

This analysis bridged the olaparib capsule and tablet formulation PK and provided key assessment to support the approval of the olaparib tablet formulation in patients with ovarian cancer, regardless of their BRCA mutation status.

Notes

Acknowledgements

The authors would like to thank the patients, their families, and all investigators and study personnel involved. They would also like to acknowledge the programmers who supported the compilation of the dataset, Mihai Surducan of Mudskipper Ltd for medical writing assistance funded by AstraZeneca, and the FDA pharmacometric reviewers Chao Liu, Jingyu Yu, and Yaning Wang for their comments. This study was sponsored by AstraZeneca.

Compliance with Ethical Standards

Funding

This study was funded by AstraZeneca.

Conflict of interest

Diansong Zhou, Maria Learoyd, Alienor Berges, Tsveta Milenkova, Nidal Al-Huniti, Helen Tomkinson, and Hongmei Xu are employees of and shareholders in AstraZeneca. Jianguo Li and Khanh Bui are former employees of AstraZeneca.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in this study.

Supplementary material

40262_2018_714_MOESM1_ESM.docx (30 kb)
Supplementary material 1 (DOCX 20 kb)

References

  1. 1.
    O’Connor MJ. Targeting the DNA damage response in cancer. Mol Cell. 2015;60:547–60.CrossRefGoogle Scholar
  2. 2.
    FDA. Lynparza prescribing information. 2018. https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/208558s001lbl.pdf. Accessed 11 June 2018.
  3. 3.
    European Medicines Agency. Lynparza (olaparib); EPAR. 2015. http://www.ema.europa.eu/ema/index.jsp?curl=/pages/medicines/human/medicines/003726/human_med_001831.jsp. Accessed 11 June 2018.
  4. 4.
    Mateo J, et al. An adaptive study to determine the optimal dose of the tablet formulation of the PARP inhibitor olaparib. Target Oncol. 2016;11:401–15.CrossRefGoogle Scholar
  5. 5.
    Mateo J, et al. DNA-repair defects and olaparib in metastatic prostate cancer. N Engl J Med. 2015;373:1697–708.CrossRefGoogle Scholar
  6. 6.
    Ang JE, et al. A mass balance study to investigate the metabolism, excretion and pharmacokinetics of [14C]-olaparib (AZD2281) in patients with advanced solid tumours refractory to standard treatments. Eur J Cancer Suppl. 2010;8:128–9.CrossRefGoogle Scholar
  7. 7.
    Dirix L, et al. Effect of itraconazole and rifampin on the pharmacokinetics of olaparib in patients with advanced solid tumors: results of two phase I open-label studies. Clin Ther. 2016;38:2286–99.CrossRefGoogle Scholar
  8. 8.
    McCormick A, Swaisland H, Reddy VP, Learoyd M, Scarfe G. In vitro evaluation of the inhibition and induction potential of olaparib, a potent poly(ADP-ribose) polymerase inhibitor, on cytochrome P450. Xenobiotica. 2018;48(6):555–64.CrossRefGoogle Scholar
  9. 9.
    Plummer R, et al. Olaparib tablet formulation: effect of food on the pharmacokinetics after oral dosing in patients with advanced solid tumours. Cancer Chemother Pharmacol. 2015;76:723–9.CrossRefGoogle Scholar
  10. 10.
    Rolfo C, et al. Effect of food on the pharmacokinetics of olaparib after oral dosing of the capsule formulation in patients with advanced solid tumors. Adv Ther. 2015;32:510–22.CrossRefGoogle Scholar
  11. 11.
    Lindbom L, Pihlgren P, Jonsson EN, Jonsson N. PsN-Toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005;79:241–57.CrossRefGoogle Scholar
  12. 12.
    Xu H, Li J, Learoyd M, Bui K, Tomkinson H, Al-Huniti N. Population pharmacokinetic (PK) and exposure haemoglobin response analysis for olaparib tablet formulation. Clin Pharmacol Ther. 2017;101(Suppl 1):S92.Google Scholar
  13. 13.
    Li J, Xu H, Learoyd M, Bui K, Tomkinson H, Al-Huniti N. Population pharmacokinetic (PopPK) and exposure response (E-R) analyses for olaparib tablet formulation in a Phase III study (SOLO2) in patients with ovarian cancer. J Pharmacokinet Pharmacodyn. 2017;44(Suppl 1):133.Google Scholar
  14. 14.
    Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011;13:143–51.CrossRefGoogle Scholar
  15. 15.
    Xu H, et al. Evaluation of aztreonam dosing regimens in patients with normal and impaired renal function: a population pharmacokinetic modeling and Monte Carlo simulation analysis. J Clin Pharmacol. 2017;57:336–44.CrossRefGoogle Scholar
  16. 16.
    Savic RM, Karlsson MO. Importance of shrinkage in empirical Bayes estimates for diagnostics: problems and solutions. AAPS J. 2009;11:558–69.CrossRefGoogle Scholar
  17. 17.
    Peer CJ, et al. Population pharmacokinetic analyses of the effect of carboplatin pretreatment on olaparib in recurrent or refractory women’s cancers. Cancer Chemother Pharmacol. 2017;80:165–75.CrossRefGoogle Scholar
  18. 18.
    Pujade-Lauraine E, et al. Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18:1274–84.CrossRefGoogle Scholar
  19. 19.
    Ledermann J, et al. Olaparib maintenance therapy in platinum-sensitive relapsed ovarian cancer. N Engl J Med. 2012;366:1382–92.CrossRefGoogle Scholar
  20. 20.
    Houk BE, et al. A population pharmacokinetic meta-analysis of sunitinib malate (SU11248) and its primary metabolite (SU12662) in healthy volunteers and oncology patients. Clin Cancer Res. 2009;15:2497–506.CrossRefGoogle Scholar
  21. 21.
    Yamamoto N, et al. A phase I, dose-finding and pharmacokinetic study of olaparib (AZD2281) in Japanese patients with advanced solid tumors. Cancer Sci. 2012;103:504–9.CrossRefGoogle Scholar
  22. 22.
    Fong PC, et al. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. N Engl J Med. 2009;361:123–34.CrossRefGoogle Scholar
  23. 23.
    Tutt A, et al. Oral poly(ADP-ribose) polymerase inhibitor olaparib in patients with BRCA1 or BRCA2 mutations and advanced breast cancer: a proof-of-concept trial. Lancet. 2010;376:235–44.CrossRefGoogle Scholar
  24. 24.
    Audeh MW, et al. Oral poly(ADP-ribose) polymerase inhibitor olaparib in patients with BRCA1 or BRCA2 mutations and recurrent ovarian cancer: a proof-of-concept trial. Lancet. 2010;376:245–51.CrossRefGoogle Scholar
  25. 25.
    Kaye SB, et al. Phase II, open-label, randomized, multicenter study comparing the efficacy and safety of olaparib, a poly(ADP-ribose) polymerase inhibitor, and pegylated liposomal doxorubicin in patients with BRCA1 or BRCA2 mutations and recurrent ovarian cancer. J Clin Oncol. 2012;30:372–9.CrossRefGoogle Scholar
  26. 26.
    Yonemori K, et al. Safety and tolerability of the olaparib tablet formulation in Japanese patients with advanced solid tumours. Cancer Chemother Pharmacol. 2016;78:525–31.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Diansong Zhou
    • 1
  • Jianguo Li
    • 1
  • Khanh Bui
    • 1
  • Maria Learoyd
    • 2
  • Alienor Berges
    • 2
  • Tsveta Milenkova
    • 3
  • Nidal Al-Huniti
    • 1
  • Helen Tomkinson
    • 2
  • Hongmei Xu
    • 1
    Email author
  1. 1.Quantitative Clinical Pharmacology, Early Clinical DevelopmentIMED Biotech Unit, AstraZenecaBostonUSA
  2. 2.Quantitative Clinical Pharmacology, Early Clinical DevelopmentIMED Biotech Unit, AstraZenecaCambridgeUK
  3. 3.Global Medicine Development, AstraZenecaCambridgeUK

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