Skip to main content

Advertisement

Log in

Model-based simulation to support the extended dosing regimens of atezolizumab

  • Pharmacokinetics and Disposition
  • Published:
European Journal of Clinical Pharmacology Aims and scope Submit manuscript

Abstract

Purpose

The currently recommended dosages of atezolizumab for patients with non-small cell lung cancer (NSCLC) and urothelial carcinoma (UC) is 840 mg every 2 weeks, 1200 mg every 3 weeks (q3w), and 1680 mg every 4 weeks (q4w). However, it has been argued that these dosages may not be optimal. This study aimed to explore the feasibility of extended dosing regimens by population pharmacokinetics (PK) simulations and exposure–response (E-R) relationships.

Methods

All simulations were conducted based on the established population PK and E-R model for safety (i.e., adverse events of special interest, AESI) and efficacy (i.e., objective response rate, ORR) for patients with NSCLC or UC. The PK, AESI, and ORR profiles of the following dosing regimens were simulated: (i) 840 mg q4w, (ii) 1200 mg every 6 weeks (q6w), and (iii) 1680 mg q8w. These regimens were compared with those of the 1200 mg q3w standard regimen.

Results

The simulation revealed that the ranking of efficacy for different extended dosing regimens were 1680 mg q8w ≅ 1200 mg q3w ≅ 1200 mg q6w > 840 mg q4w based on the predicted probability of ORR in patients with NSCLC and UC, and this ranking order was similar to that of the safety outcome of the AESI. The minimum serum concentration at steady-state (Cmin,ss) values for all dosing regimens was all higher than the target effective concentration of 6 μg/mL.

Conclusion

The findings from this simulation suggest that extended dosing regimens are unlikely to significantly impair clinical outcomes and may provide more therapeutic benefits to patients in terms of safety.

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

Similar content being viewed by others

Data availability

All data was generated from the published model.

References

  1. Fehrenbacher L, Spira A, Ballinger M, Kowanetz M, Vansteenkiste J, Mazieres J, Park K, Smith D, Artal-Cortes A, Lewanski C, Braiteh F, Waterkamp D, He P, Zou W, Chen DS, Yi J, Sandler A, Rittmeyer A (2016) Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer (POPLAR): a multicentre, open-label, phase 2 randomised controlled trial. Lancet 387(10030):1837–1846. https://doi.org/10.1016/s0140-6736(16)00587-0

    Article  CAS  PubMed  Google Scholar 

  2. Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, Dawson N, O’Donnell PH, Balmanoukian A, Loriot Y, Srinivas S, Retz MM, Grivas P, Joseph RW, Galsky MD, Fleming MT, Petrylak DP, Perez-Gracia JL, Burris HA, Castellano D, Canil C, Bellmunt J, Bajorin D, Nickles D, Bourgon R, Frampton GM, Cui N, Mariathasan S, Abidoye O, Fine GD, Dreicer R (2016) Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet 387(10031):1909–1920. https://doi.org/10.1016/s0140-6736(16)00561-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Morrissey KM, Marchand M, Patel H, Zhang R, Wu B, Phyllis Chan H, Mecke A, Girish S, Jin JY, Winter HR, Bruno R (2019) Alternative dosing regimens for atezolizumab: an example of model-informed drug development in the postmarketing setting. Cancer Chemother Pharmacol 84(6):1257–1267. https://doi.org/10.1007/s00280-019-03954-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Freshwater T, Kondic A, Ahamadi M, Li CH, de Greef R, de Alwis D, Stone JA (2017) Evaluation of dosing strategy for pembrolizumab for oncology indications. J Immunother Cancer 5:43. https://doi.org/10.1186/s40425-017-0242-5

    Article  PubMed  PubMed Central  Google Scholar 

  5. Long GV, Tykodi SS, Schneider JG, Garbe C, Gravis G, Rashford M, Agrawal S, Grigoryeva E, Bello A, Roy A, Rollin L, Zhao X (2018) Assessment of nivolumab exposure and clinical safety of 480 mg every 4 weeks flat-dosing schedule in patients with cancer. Ann Oncol 29(11):2208–2213. https://doi.org/10.1093/annonc/mdy408

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Novakovic AM, Wilkins JJ, Dai H, Wade JR, Neuteboom B, Brar S, Bello CL, Girard P, Khandelwal A (2019) Changing body weight-based dosing to a flat dose for avelumab in metastatic Merkel cell and advanced urothelial carcinoma. Clin Pharmacol Ther 107:588–596. https://doi.org/10.1002/cpt.1645

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Staab A, Rook E, Maliepaard M, Aarons L, Benson C (2013) Modeling and simulation in clinical pharmacology and dose finding. CPT Pharmacometrics Syst Pharmacol 2:e29. https://doi.org/10.1038/psp.2013.5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. TGA. Extract from the Clinical Evaluation Report for Atezolizumab. 2017. https://www.tga.gov.au/sites/default/files/auspar-atezolizumab-180903-cer.pdf. Accessed date: 2 January 2020.

  9. Stroh M, Winter H, Marchand M, Claret L, Eppler S, Ruppel J, Abidoye O, Teng SL, Lin WT, Dayog S, Bruno R, Jin J, Girish S (2017) Clinical pharmacokinetics and pharmacodynamics of atezolizumab in metastatic urothelial carcinoma. Clin Pharmacol Ther 102(2):305–312. https://doi.org/10.1002/cpt.587

    Article  CAS  PubMed  Google Scholar 

  10. Goldstein DA, Ratain MJ (2019) Alternative dosing regimens for atezolizumab: right dose, wrong frequency. Cancer Chemother Pharmacol 84(6):1153–1155. https://doi.org/10.1007/s00280-019-03971-7

    Article  PubMed  Google Scholar 

  11. Deng R, Bumbaca D, Pastuskovas CV, Boswell CA, West D, Cowan KJ, Chiu H, McBride J, Johnson C, Xin Y, Koeppen H, Leabman M, Iyer S (2016) Preclinical pharmacokinetics, pharmacodynamics, tissue distribution, and tumor penetration of anti-PD-L1 monoclonal antibody, an immune checkpoint inhibitor. mAbs 8(3):593–603. https://doi.org/10.1080/19420862.2015.1136043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. FDA. Clinical pharmacology biopharmaceutics review(s) for atezolizumab. 2016. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2016/761034Orig1s000MedR.pdf, Accessed date: 2 January 2020.

  13. Ratain MJ, Goldstein DA (2018) Time is money: optimizing the scheduling of nivolumab. J Clin Oncol. https://doi.org/10.1200/jco.18.00045

  14. Renner A, Burotto M, Rojas C (2019) Immune checkpoint inhibitor dosing: can we go lower without compromising clinical efficacy? J Global Oncol (5):1–5. https://doi.org/10.1200/jgo.19.00142

  15. Ogungbenro K, Patel A, Saunders M, Clark J, Duncombe R (2019) An evaluation of cetuximab dosing strategies using pharmacokinetics and cost analysis. J Pharm Pharmacol 71(8):1222–1230. https://doi.org/10.1111/jphp.13108

    Article  CAS  PubMed  Google Scholar 

  16. Peer CJ, Goldstein DA, Goodell JC, Nguyen R, Figg WD, Ratain MJ (2020) Opportunities for using in silico-based extended dosing regimens for monoclonal antibody immune checkpoint inhibitors. Br J Clin Pharmacol. https://doi.org/10.1111/bcp.14369

  17. FDA. Exposure-Response Relationships-Study Design, Data Analysis, and Regulatory Applications. 2003. https://www.fda.gov/media/71277/download. Accessed date: 24 June 2020.

  18. FDA. Clinical trial endpoints for the approval of cancer drugs and biologics. 2018. https://www.fda.gov/media/71195/download. Accessed date: 2 January 2020.

  19. Fleming TR (2005) Objective response rate as a surrogate end point: a commentary. J Clin Oncol 23(22):4845–4846. https://doi.org/10.1200/jco.2005.92.008

    Article  PubMed  Google Scholar 

  20. Ito K, Miura S, Sakaguchi T, Murotani K, Horita N, Akamatsu H, Uemura K, Morita S, Yamamoto N (2019) The impact of high PD-L1 expression on the surrogate endpoints and clinical outcomes of anti-PD-1/PD-L1 antibodies in non-small cell lung cancer. Lung Cancer (Amsterdam) 128:113–119. https://doi.org/10.1016/j.lungcan.2018.12.023

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. Min-Shung Lin for his careful reading of manuscript and helpful suggestions.

Author information

Authors and Affiliations

Authors

Contributions

LFH wrote the manuscript and designed research; CCH analyzed data.

Corresponding author

Correspondence to Li-Feng Hsu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics approval

Not applicable.

Disclaimer

The views expressed in this article are the author’s personal opinions and not necessarily recommendations of the Taiwan CDE.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chou, CH., Hsu, LF. Model-based simulation to support the extended dosing regimens of atezolizumab. Eur J Clin Pharmacol 77, 87–93 (2021). https://doi.org/10.1007/s00228-020-02980-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00228-020-02980-3

Keywords

Navigation