Skip to main content
SpringerLink
Log in

Population pharmacokinetics of lenalidomide in multiple myeloma patients

  • Original Article
  • Published:
Cancer Chemotherapy and Pharmacology Aims and scope Submit manuscript

Abstract

Purpose

Lenalidomide disease-specific toxicity profiles and potentially life-threatening adverse events support the consideration of diversity in starting doses. The aim of this study was to conduct a population pharmacokinetic analysis of lenalidomide in multiple myeloma patients to identify and evaluate non-studied covariates that could be used for dose individualization.

Methods

Blood samples were collected from 15 multiple myeloma patients. Nonlinear mixed-effects modeling was used to develop a population pharmacokinetic model and perform covariate analysis. The developed model was used to simulate dose schedules in order to explore the need of different dosing regimens in patients with different covariate values.

Results

The data were accurately described by a one-compartment model with first-order elimination. Absorption was best described using three transit compartments. Creatinine clearance and body surface area were identified as covariates affecting apparent clearance and apparent volume of distribution, respectively. Simulations revealed that lower starting doses than the standard 25 mg/daily could be used in patients with body surface area below 1.8 m2 and even higher doses might be necessary for patients with normal renal function and large body surface area.

Conclusions

This study identified creatinine clearance and body surface area as covariates that have a clinically relevant impact on lenalidomide pharmacokinetics using population pharmacokinetics. In addition, the developed population pharmacokinetic model can be used to individualize lenalidomide dose in multiple myeloma patients, taking into account not only creatinine clearance but also body surface area.

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
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Kotla V, Goel S, Nischal S et al (2009) Mechanism of action of lenalidomide in hematological malignancies. J Hematol Oncol 2:36. doi:10.1186/1756-8722-2-36

    Article  PubMed  PubMed Central  Google Scholar 

  2. Quach H, Ritchie D, Stewart AK et al (2010) Mechanism of action of immunomodulatory drugs (IMiDS) in multiple myeloma. Leukemia 24:22–32. doi:10.1038/leu.2009.236

    Article  CAS  PubMed  Google Scholar 

  3. Richardson PG, Schlossman RL, Weller E et al (2002) Immunomodulatory drug CC-5013 overcomes drug resistance and is well tolerated in patients with relapsed multiple myeloma. Blood 100:3063–3067. doi:10.1182/blood-2002-03-0996

    Article  CAS  PubMed  Google Scholar 

  4. Weber DM, Chen C, Niesvizky R et al (2007) Lenalidomide plus dexamethasone for relapsed multiple myeloma in North America. N Engl J Med 357:2133–2142. doi:10.1056/NEJMoa070596

    Article  CAS  PubMed  Google Scholar 

  5. Dimopoulos M, Spencer A, Attal M et al (2007) Lenalidomide plus dexamethasone for relapsed or refractory multiple myeloma. N Engl J Med 357:2123–2132. doi:10.1056/NEJMoa070594

    Article  CAS  PubMed  Google Scholar 

  6. Seiffert M (2014) Lenalidomide, an antiproliferative CLL drug. Blood 124:1545–1546. doi:10.1182/blood-2014-07-587360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fowler NH, Davis RE, Rawal S et al (2014) Safety and activity of lenalidomide and rituximab in untreated indolent lymphoma: an open-label, phase 2 trial. Lancet Oncol 15:1311–1318. doi:10.1016/S1470-2045(14)70455-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bejar R, Steensma DP (2014) Recent developments in myelodysplastic syndromes. Blood 124:2793–2803. doi:10.1182/blood-2014-04-522136

    Article  CAS  PubMed  Google Scholar 

  9. Rao KV (2007) Lenalidomide in the treatment of multiple myeloma. Am J Health Syst Pharm 64:1799–1807. doi:10.2146/ajhp070029

    Article  CAS  PubMed  Google Scholar 

  10. Andritsos LA, Johnson AJ, Lozanski G et al (2008) Higher doses of lenalidomide are associated with unacceptable toxicity including life-threatening tumor flare in patients with chronic lymphocytic leukemia. J Clin Oncol 26:2519–2525. doi:10.1200/JCO.2007.13.9709

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Palumbo A, Falco P, Corradini P et al (2007) Melphalan, prednisone, and lenalidomide treatment for newly diagnosed myeloma: a report from the GIMEMA–Italian Multiple Myeloma Network. J Clin Oncol 25:4459–4465. doi:10.1200/JCO.2007.12.3463

    Article  CAS  PubMed  Google Scholar 

  12. Berg SL, Cairo MS, Russell H et al (2011) Safety, pharmacokinetics, and immunomodulatory effects of lenalidomide in children and adolescents with relapsed/refractory solid tumors or myelodysplastic syndrome: a Children’s Oncology Group Phase I Consortium report. J Clin Oncol 29:316–323. doi:10.1200/JCO.2010.30.8387

    Article  CAS  PubMed  Google Scholar 

  13. Grzasko N, Morawska M, Hus M (2015) Optimizing the treatment of patients with multiple myeloma and renal impairment. Clin Lymphoma Myeloma Leuk 15:187–198. doi:10.1016/j.clml.2014.09.012

    Article  PubMed  Google Scholar 

  14. Kado Y, Kitazawa F, Tsujimoto M et al (2015) Prediction of the lenalidomide toxicity and its therapeutic efficacy in Japanese multiple myeloma patients by measuring its plasma concentration. Blood 126:3700

    Google Scholar 

  15. EMA (2007) Revlimid, INN-lenalidomide EPAR scientific discussion. http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Scientific_Discussion/human/000717/WC500056022.pdf. Accessed 25 Dec 2016

  16. Chen N, Lau H, Kong L et al (2007) Pharmacokinetics of lenalidomide in subjects with various degrees of renal impairment and in subjects on hemodialysis. J Clin Pharmacol 47:1466–1475. doi:10.1177/0091270007309563

    Article  CAS  PubMed  Google Scholar 

  17. Klein U, Neben K, Hielscher T et al (2011) Lenalidomide in combination with dexamethasone: effective regimen in patients with relapsed or refractory multiple myeloma complicated by renal impairment. Ann Hematol 90:429–439. doi:10.1007/s00277-010-1080-4

    Article  CAS  PubMed  Google Scholar 

  18. Hou J, Du X, Jin J et al (2013) A multicenter, open-label, phase 2 study of lenalidomide plus low-dose dexamethasone in Chinese patients with relapsed/refractory multiple myeloma: the MM-021 trial. J Hematol Oncol 6:41. doi:10.1186/1756-8722-6-41

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Iida S, Chou T, Okamoto S et al (2010) Lenalidomide plus dexamethasone treatment in Japanese patients with relapsed/refractory multiple myeloma. Int J Hematol 92:118–126. doi:10.1007/s12185-010-0624-7

    Article  CAS  PubMed  Google Scholar 

  20. Ette E, Zhou S, Weiss D, Palmisano M (2013) Population pharmacokinetics and exposure-safety of lenalidomide in patients with multiple myeloma, myelodysplastic syndromes and mantle cell lymphoma. Blood 122:3234

    Google Scholar 

  21. Shida S, Takahashi N, Miura M et al (2014) A limited sampling model to estimate exposure to lenalidomide in multiple myeloma patients. Ther Drug Monit 36:505–509. doi:10.1097/FTD.0000000000000034

    Article  CAS  PubMed  Google Scholar 

  22. Guglieri-Lopez B, Perez-Pitarch A, Martinez-Gomez MA et al (2016) A wide linearity range method for the determination of lenalidomide in plasma by high-performance liquid chromatography: application to pharmacokinetic studies. J Lab Autom. doi:10.1177/2211068216636570

    PubMed  Google Scholar 

  23. Beal S, Sheiner L, Boeckmann A (2006) NONMEM users guide (1989–2006). Icon Development Solutions, Ellicott City, USA

  24. Lindbom L, Pihlgren P, Jonsson N (2005) PsN-toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 79:241–257. doi:10.1016/j.cmpb.2005.04.005

    Article  PubMed  Google Scholar 

  25. Keizer RJ, van Benten M, Beijnen JH et al (2011) Pirana and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed 101:72–79. doi:10.1016/j.cmpb.2010.04.018

    Article  PubMed  Google Scholar 

  26. Keizer RJ, Jansen RS, Rosing H et al (2015) Incorporation of concentration data below the limit of quantification in population pharmacokinetic analyses. Pharmacol Res Perspect 3:e00131. doi:10.1002/prp2.131

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bergstrand M, Hooker AC, Wallin JE, Karlsson MO (2011) Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J 13:143–151. doi:10.1208/s12248-011-9255-z

    Article  PubMed  PubMed Central  Google Scholar 

  28. Chen N, Zhou S, Palmisano M (2016) Clinical pharmacokinetics and pharmacodynamics of lenalidomide. Clin Pharmacokinet. doi:10.1007/s40262-016-0432-1

    PubMed Central  Google Scholar 

  29. Tunblad K, Lindbom L, McFadyen L et al (2008) The use of clinical irrelevance criteria in covariate model building with application to dofetilide pharmacokinetic data. J Pharmacokinet Pharmacodyn 35:503–526. doi:10.1007/s10928-008-9099-z

    Article  CAS  PubMed  Google Scholar 

  30. Chen N, Kasserra C, Reyes J et al (2012) Single-dose pharmacokinetics of lenalidomide in healthy volunteers: dose proportionality, food effect, and racial sensitivity. Cancer Chemother Pharmacol 70:717–725. doi:10.1007/s00280-012-1966-z

    Article  CAS  PubMed  Google Scholar 

  31. Ribbing J, Jonsson EN (2004) Power, selection bias and predictive performance of the Population Pharmacokinetic Covariate Model. J Pharmacokinet Pharmacodyn 31:109–134

    Article  CAS  PubMed  Google Scholar 

  32. Myeloma incidence statistics—Cancer Research UK. http://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/myeloma/incidence. Accessed 17 Aug 2016

Download references

Acknowledgements

We thank patients with multiple myeloma for participating in this study and healthcare staff from Pharmacy and Hematology Department of Doctor Peset University Hospital for their support.

Funding

This work was supported by the Foundation for the Promotion of Health and Biomedical Research of the Valencian Community (FISABIO).

Author contribution

BG-L performed the data analysis and wrote the manuscript. AP-P, DJM, BP-O, MC-M, H-JG and MM-S contributed in the data analysis and revised the manuscript.

Author information

Authors and Affiliations

  1. Pharmacy Department, Doctor Peset University Hospital of Valencia, Gaspar Aguilar Avenue, 90, 46017, Valencia, Spain

    Beatriz Guglieri-López, Begoña Porta-Oltra & Mónica Climente-Martí

  2. Pharmacy Department, University Clinical Hospital of Valencia, Blasco Ibañez Avenue, 17, 46010, Valencia, Spain

    Alejandro Pérez-Pitarch

  3. Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands

    Dirk Jan A. R. Moes & Henk Jan Guchelaar

  4. Department of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, University of Valencia, Vicent Andrés Estellés Avenue, 46100, Burjassot, Valencia, Spain

    Matilde Merino-Sanjuán

  5. Molecular Recognition and Technological Development Institute, Centro Mixto Universidad Politécnica de Valencia-Universidad de Valencia, Valencia, Spain

    Matilde Merino-Sanjuán

Authors
  1. Beatriz Guglieri-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alejandro Pérez-Pitarch
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dirk Jan A. R. Moes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Begoña Porta-Oltra
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mónica Climente-Martí
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Henk Jan Guchelaar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Matilde Merino-Sanjuán
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Beatriz Guglieri-López.

Ethics declarations

Conflict of interest

Beatriz Guglieri-López, Alejandro Pérez-Pitarch, Dirk Jan Moes, Begoña Porta-Oltra, Mónica Climente-Martí, Henk-Jan Guchelaar and Matilde Merino-Sanjuán have no conflicts of interest that might be relevant to the content of this manuscript.

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 Declaration of Helsinki and its later amendments or comparable ethical standards.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 60 kb)

Supplementary material 2 (DOCX 53 kb)

280_2016_3228_MOESM3_ESM.tiff

Schematic representation of the pharmacokinetic model for lenalidomide. A linear one-compartment model with first-order absorption and elimination, including three transit compartments to describe the absorption phase (TIFF 1521 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guglieri-López, B., Pérez-Pitarch, A., Moes, D.J.A.R. et al. Population pharmacokinetics of lenalidomide in multiple myeloma patients. Cancer Chemother Pharmacol 79, 189–200 (2017). https://doi.org/10.1007/s00280-016-3228-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00280-016-3228-y

Keywords

Search

Navigation