Skip to main content
SpringerLink
Log in

Population Pharmacokinetics and Pharmacodynamics of Carfilzomib in Combination with Rituximab, Ifosfamide, Carboplatin, and Etoposide in Adult Patients with Relapsed/Refractory Diffuse Large B Cell Lymphoma

  • Original Research Article
  • Published:
Targeted Oncology Aims and scope Submit manuscript

Abstract

Background

In patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL), salvage chemotherapy regimens (e.g., rituximab, ifosfamide, carboplatin, and etoposide, R-ICE) yield poor outcomes. Carfilzomib, an irreversible proteasome inhibitor, can overcome acquired rituximab-chemotherapy resistance and, when combined with R-ICE, improves outcomes in patients with R/R DLBCL.

Objective

This analysis aimed to develop a population pharmacokinetic/pharmacodynamic (PK/PD) model for carfilzomib in R/R DLBCL patients.

Patients and Methods

In a single-center, open-label, prospective phase 1 study, patients received carfilzomib (10, 15, or 20 mg/m2) on days 1, 2, 8, and 9, and standard doses of R-ICE on days 3–6 every 21 days (maximum of three cycles). Carfilzomib plasma concentrations up to 24 h postinfusion were measured by liquid chromatography coupled with tandem mass spectrometry. Proteasome activity (PD biomarker) in peripheral blood mononuclear cells was assessed on days 1–2 with sparse sampling. PK/PD models were developed using NONMEM v7.4.1 interfaced with Finch Studio v1.1.0 and PsN v4.7.0. Model selection was guided by objective function value, goodness‐of‐fit, and visual predictive checks. Stepwise covariate modeling was used for covariate selection.

Results

Twenty-eight patients were enrolled in the PK/PD analysis, from whom 217 PK samples and 127 PD samples were included. Carfilzomib PK was best described by a two-compartment model with linear disposition (typical total clearance of 133 L/h). Proteasome activity was best characterized using a turnover model with irreversible inactivation. All parameters were estimated with good precision. No statistically significant covariates were identified.

Conclusions

A validated population-based PK/PD model of carfilzomib was developed successfully. Further research is needed to identify sources of variability in response to treatment with carfilzomib in combination with R-ICE.

Clinical Trial Registration

ClinicalTrials.gov identifier number NCT01959698.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Roschewski M, Phelan JD, Wilson WH. Molecular classification and treatment of diffuse large B-cell lymphoma and primary mediastinal B-cell lymphoma. Cancer J. 2020;26(3):195–205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Coiffier B, Thieblemont C, Van Den Neste E, Lepeu G, Plantier I, Castaigne S, et al. Long-term outcome of patients in the LNH-98.5 trial, the first randomized study comparing rituximab-CHOP to standard CHOP chemotherapy in DLBCL patients: a study by the Groupe d'Etudes des Lymphomes de l'Adulte. Blood. 2010;116(12):2040–5.

  3. Friedberg JW. Relapsed/refractory diffuse large B-cell lymphoma. Hematol Am Soc Hematol Educ Program. 2011;2011:498–505.

    Article  Google Scholar 

  4. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology - B-Cell Lymphomas, Version 2.2023. 2023. https://www.nccn.org/professionals/physician_gls/pdf/b-cell.pdf. Accessed 1 May 2023.

  5. Gisselbrecht C, Glass B, Mounier N, Singh Gill D, Linch DC, Trneny M, et al. Salvage regimens with autologous transplantation for relapsed large B-cell lymphoma in the rituximab era. J Clin Oncol. 2010;28(27):4184–90.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Olejniczak SH, Blickwedehl J, Belicha-Villanueva A, Bangia N, Riaz W, Mavis C, et al. Distinct molecular mechanisms responsible for bortezomib-induced death of therapy-resistant versus-sensitive B-NHL cells. Blood. 2010;116(25):5605–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Olejniczak SH, Hernandez-Ilizaliturri FJ, Clements JL, Czuczman MS. Acquired resistance to rituximab is associated with chemotherapy resistance resulting from decreased Bax and Bak expression. Clin Cancer Res. 2008;14(5):1550–60.

    Article  CAS  PubMed  Google Scholar 

  8. Goy A, Younes A, McLaughlin P, Pro B, Romaguera JE, Hagemeister F, et al. Phase II study of proteasome inhibitor bortezomib in relapsed or refractory B-cell non-Hodgkin’s lymphoma. J Clin Oncol. 2005;23(4):667–75.

    Article  CAS  PubMed  Google Scholar 

  9. Kane RC, Dagher R, Farrell A, Ko CW, Sridhara R, Justice R, et al. Bortezomib for the treatment of mantle cell lymphoma. Clin Cancer Res. 2007;13(18 Pt 1):5291–4.

    Article  CAS  PubMed  Google Scholar 

  10. O’Connor OA. Targeting histones and proteasomes: new strategies for the treatment of lymphoma. J Clin Oncol. 2005;23(26):6429–36.

    Article  CAS  PubMed  Google Scholar 

  11. Strauss SJ, Maharaj L, Hoare S, Johnson PW, Radford JA, Vinnecombe S, et al. Bortezomib therapy in patients with relapsed or refractory lymphoma: potential correlation of in vitro sensitivity and tumor necrosis factor alpha response with clinical activity. J Clin Oncol. 2006;24(13):2105–12.

    Article  CAS  PubMed  Google Scholar 

  12. Younes A, Pro B, Fayad L. Experience with bortezomib for the treatment of patients with relapsed classical Hodgkin lymphoma. Blood. 2006;107(4):1731–2.

    Article  CAS  PubMed  Google Scholar 

  13. Dunleavy K, Pittaluga S, Czuczman MS, Dave SS, Wright G, Grant N, et al. Differential efficacy of bortezomib plus chemotherapy within molecular subtypes of diffuse large B-cell lymphoma. Blood. 2009;113(24):6069–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Fowler N, Kahl BS, Lee P, Matous JV, Cashen AF, Jacobs SA, et al. Bortezomib, bendamustine, and rituximab in patients with relapsed or refractory follicular lymphoma: the phase II VERTICAL study. J Clin Oncol. 2011;29(25):3389–95.

    Article  CAS  PubMed  Google Scholar 

  15. Robak T, Huang H, Jin J, Zhu J, Liu T, Samoilova O, et al. Bortezomib-based therapy for newly diagnosed mantle-cell lymphoma. N Engl J Med. 2015;372(10):944–53.

    Article  CAS  PubMed  Google Scholar 

  16. Gu JJ, Hernandez-Ilizaliturri FJ, Kaufman GP, Czuczman NM, Mavis C, Skitzki JJ, et al. The novel proteasome inhibitor carfilzomib induces cell cycle arrest, apoptosis and potentiates the anti-tumour activity of chemotherapy in rituximab-resistant lymphoma. Br J Haematol. 2013;162(5):657–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Torka P, Groman A, Wong J, Nichols J, Kader A, Mavis C, et al. Carfilzomib combined with rituximab, ifosfamide, carboplatin, and etoposide for relapsed or refractory DLBCL. Blood Adv. 2023;7(7):1146–55.

    Article  CAS  PubMed  Google Scholar 

  18. Ou Y, Doshi S, Nguyen A, Jonsson F, Aggarwal S, Rajangam K, et al. Population pharmacokinetics and exposure-response relationship of carfilzomib in patients with multiple myeloma. J Clin Pharmacol. 2017;57(5):663–77.

    Article  CAS  PubMed  Google Scholar 

  19. European Medicines Agency-Committee for Medicinal Products for Human Use. Group of Variations Including an Extension of Indication Assessment Report: Carfilzomib. 2016. https://www.ema.europa.eu/en/documents/variation-report/kyprolis-h-c-3790-ii-0001-g-epar-assessment-report-variation_en.pdf. Accessed 24 May 2022.

  20. US Food and Drug Administration-Center for Drug Evaluation and Research. Clinical Pharmacology and Biopharmaceutics Review(s): Carfilzomib. 2011. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2012/202714Orig1s000ClinPharmR.pdf. Accessed 24 May 2022.

  21. Yago MR, Mehta K, Bose M, Bhagwat S, Chopra VS, Dutta S, et al. Mechanistic pharmacokinetic/pharmacodynamic modeling in support of a patient-convenient, longer dosing interval for carfilzomib, a covalent inhibitor of the proteasome. Clin Pharmacokinet. 2023;62(5):779–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. US Food and Drug Administration. Bioanalytical Method Validation: Guidance for Industry. 2018. https://www.fda.gov/files/drugs/published/Bioanalytical-Method-Validation-Guidance-for-Industry.pdf. Accessed 17 May 2022.

  23. Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn. 2001;28(5):481–504.

    Article  CAS  PubMed  Google Scholar 

  24. Upton RN, Mould DR. Basic concepts in population modeling, simulation, and model-based drug development: part 3-introduction to pharmacodynamic modeling methods. CPT Pharmacometrics Syst Pharmacol. 2014;3(1): e88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Janssen JM, Dorlo TPC, Niewerth D, Wilhelm AJ, Zwaan CM, Beijnen JH, et al. A semi-mechanistic population pharmacokinetic/pharmacodynamic model of bortezomib in pediatric patients with relapsed/refractory acute lymphoblastic leukemia. Clin Pharmacokinet. 2020;59(2):207–16.

    Article  CAS  PubMed  Google Scholar 

  26. Mould DR, Upton RN. Basic concepts in population modeling, simulation, and model-based drug development-part 2: introduction to pharmacokinetic modeling methods. CPT Pharmacometrics Syst Pharmacol. 2013;2(4): e38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Overgaard RV, Ingwersen SH, Tornoe CW. Establishing good practices for exposure-response analysis of clinical endpoints in drug development. CPT Pharmacometrics Syst Pharmacol. 2015;4(10):565–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhang L, Mager DE. Physiologically-based pharmacokinetic modeling of target-mediated drug disposition of bortezomib in mice. J Pharmacokinet Pharmacodyn. 2015;42(5):541–52.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was funded by Amgen and the National Cancer Institute (NCI) grant P30CA016056 involving the use of Roswell Park Comprehensive Cancer Center’s BMPK Shared Resource. We thank Dr. Thibaud Derippe (University of Buffalo at the time of analysis, currently with AstraZeneca) and Dr. Mfonabasi Ette (University at Buffalo) and Dr. Mohamed Ismail (Enhanced Pharmacodynamics, LLC) for their technical support during the development of the PK/PD model. Also, we are thankful to Dr. Alan Hutson (Dept. of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center) for providing helpful biostatistical advice and input.

Author information

Authors and Affiliations

  1. Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA

    Lan-Hsi Lin & Donald E. Mager

  2. Bioanalytics, Metabolomics, and Pharmacokinetics Shared Resource, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA

    Lan-Hsi Lin, Mohammad Ghasemi, Sarah M. Burke & Andrew K. L. Goey

  3. Department of Medicine-Lymphoma, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA

    Cory K. Mavis, Pallawi Torka & Francisco J. Hernandez-Ilizaliturri

  4. Clinical Research Services, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA

    Jenna R. Nichols

  5. Department of Pharmacology and Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA

    Mohammad Ghasemi & Andrew K. L. Goey

Authors
  1. Lan-Hsi Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammad Ghasemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sarah M. Burke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cory K. Mavis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jenna R. Nichols
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pallawi Torka
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Donald E. Mager
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Francisco J. Hernandez-Ilizaliturri
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Andrew K. L. Goey
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andrew K. L. Goey.

Ethics declarations

Funding

This work was funded by Amgen and the National Cancer Institute (NCI) grant P30CA016056 involving the use of Roswell Park Comprehensive Cancer Center’s BMPK Shared Resource.

Conflict of Interest

P.T. received consulting fees from ADC therapeutics, TG therapeutics, Genmab, Genentech, Lilly USA, and Seagen. F.J.H.I. is an advisory Board Member for Amgen, Karyopharm Therapeutics, Celgene Corporation, Kura Oncology, AbbVie Inc., Seattle Genetics Inc., Epizyme, Pharmacyclics, Gilead, Kite Pharma, Novartis, and MorphoSys. F.J.H.I. also is a member of the Speaker Bureau of MorphoSys. Lan-Hsi Lin, Mohammad Ghasemi, Sarah M. Burke, Cory K. Mavis, Jenna R. Nichols, Donald E. Mager, and Andrew K.L. Goey declare that they have no conflicts of interest that might be relevant to the contents of this manuscript.

Ethics Approval

The clinical study was performed per the International Council for Harmonization Good Clinical Practice Guideline and the ethical principles of the Declaration of Helsinki and was approved by the institutional review board of Roswell Park Comprehensive Cancer Center (protocol no. I-240813).

Consent to Participate

All patients provided written informed consent prior to enrollment in the study.

Consent for Publication

Not applicable.

Data Availability

The NONMEM control stream for nonlinear-mixed effect PK/PD modeling has been made available in Supplementary File S6.

Author Contributions

DEM, FJHI, and AKLG designed the project and provided supervision; LL and MG developed the PK/PD model and performed the data analysis; SMB performed the LC–MS/MS analysis; CKM performed the proteasome activity analysis; JRN, PT, and FJHI collected clinical data; FJHI acquired funding; DEM, FJHI, and AKLG supported interpretation of the results; LL and A.K.L.G. wrote the original draft; and all authors critically read, revised, and approved the final manuscript.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 480 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, LH., Ghasemi, M., Burke, S.M. et al. Population Pharmacokinetics and Pharmacodynamics of Carfilzomib in Combination with Rituximab, Ifosfamide, Carboplatin, and Etoposide in Adult Patients with Relapsed/Refractory Diffuse Large B Cell Lymphoma. Targ Oncol 18, 685–695 (2023). https://doi.org/10.1007/s11523-023-00992-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11523-023-00992-4

Search

Navigation