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A Semi-Mechanistic Population Pharmacokinetic/Pharmacodynamic Model of Bortezomib in Pediatric Patients with Relapsed/Refractory Acute Lymphoblastic Leukemia

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Abstract

Introduction

The pharmacokinetics (PK) of the 20S proteasome inhibitor bortezomib are characterized by a large volume of distribution and a rapid decline in plasma concentrations within the first hour after administration. An increase in exposure was observed in the second week of treatment, which has previously been explained by extensive binding of bortezomib to proteasome in erythrocytes and peripheral tissues. We characterized the nonlinear population PK and pharmacodynamics (PD) of bortezomib in children with acute lymphoblastic leukemia.

Methods

Overall, 323 samples from 28 patients were available from a pediatric clinical study investigating bortezomib at an intravenous dose of 1.3 mg/m2 twice weekly (Dutch Trial Registry number 1881/ITCC021). A semi-physiological PK model for bortezomib was first developed; the PK were linked to the decrease in 20S proteasome activity in the final PK/PD model.

Results

The plasma PK data were adequately described using a two-compartment model with linear elimination. Increased concentrations were observed in week 2 compared with week 1, which was described using a Langmuir binding model. The decrease in 20S proteasome activity was best described by a direct effect model with a sigmoidal maximal inhibitory effect, representing the relationship between plasma concentrations and effect. The maximal inhibitory effect was 0.696 pmol AMC/s/mg protein (95% confidence interval 0.664–0.728) after administration.

Conclusion

The semi-physiological model adequately described the nonlinear PK and PD of bortezomib in plasma. This model can be used to further optimize dosing of bortezomib.

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References

  1. Pui C-H, Yang JJ, Hunger SP, Pieters R, Schrappe M, Biondi A, et al. Childhood acute lymphoblastic leukemia: progress through collaboration. J Clin Oncol. 2015;33:2938–48.

    PubMed  PubMed Central  CAS  Google Scholar 

  2. Moreno L, Pearson ADJ, Paoletti X, Jimenez I, Geoerger B, Kearns PR, et al. Early phase clinical trials of anticancer agents in children and adolescents—an ITCC perspective. Nat Rev Clin Oncol. 2017;14:497–507.

    PubMed  CAS  Google Scholar 

  3. Bross PF, Kane R, Farrell AT, Abraham S, Benson K, Brower ME, et al. Approval summary for bortezomib for injection in the treatment of multiple myeloma. Clin Cancer Res. 2004;10(2 Pt 1):3954–64.

    PubMed  CAS  Google Scholar 

  4. Tan CRC, Abdul-Majeed S, Cael B, Barta SK. Clinical pharmacokinetics and pharmacodynamics of bortezomib. Clin Pharmacokinet. 2019;58(2):157–68.

    PubMed  CAS  Google Scholar 

  5. Houghton PJ, Morton CL, Kolb EA, Lock R, Carol H, Reynolds CP, et al. Initial testing (stage 1) of the proteasome inhibitor bortezomib by the pediatric preclinical testing program. Pediatr Blood Cancer. 2008;50:37–45.

    PubMed  Google Scholar 

  6. Reece DE, Sullivan D, Lonial S, Mohrbacher AF, Chatta G, Shustik C, et al. Pharmacokinetic and pharmacodynamic study of two doses of bortezomib in patients with relapsed multiple myeloma. Cancer Chemother Pharmacol. 2011;67:57–67.

    PubMed  CAS  Google Scholar 

  7. Horton TM, Pati D, Plon SE, Thompson PA, Bomgaars LR, Adamson PC, et al. A phase 1 study of the proteasome inhibitor bortezomib in pediatric patients with refractory leukemia: a Children’s Oncology Group study. Clin Cancer Res. 2007;13:1516–22.

    PubMed  CAS  Google Scholar 

  8. Muscal JA, Thompson PA, Horton TM, Ingle AM, Ahern CH, McGovern RM, et al. A Phase I trial of vorinostat and bortezomib in children with refractory or recurrent solid tumors: a Children’s Oncology Group Phase I Consortium Study (ADVL0916). Pediatr Blood Cancer. 2013;60:390–5.

    PubMed  CAS  Google Scholar 

  9. Blaney SM, Bernstein M, Neville K, Ginsberg J, Kitchen B, Horton T, et al. Phase I study of the proteasome inhibitor bortezomib in pediatric patients with refractory solid tumors: a Children’s Oncology Group Study (ADVL0015). J Clin Oncol. 2004;22:4804–6.

    PubMed  CAS  Google Scholar 

  10. Hanley MJ, Mould DR, Taylor TJ, Gupta N, Suryanarayan K, Neuwirth R, et al. Population pharmacokinetic analysis of bortezomib in pediatric leukemia patients: model-based support for body surface area-based dosing over the 2- to 16-year age range. J Clin Pharmacol. 2017;57(9):1183–93.

    PubMed  PubMed Central  CAS  Google Scholar 

  11. Kaspers GJL, Niewerth D, Wilhelm BAJ, Scholte-van Houtem P, Lopez-Yurda M, Berkhof J, et al. An effective modestly intensive re-induction regimen with bortezomib in relapsed or refractory paediatric acute lymphoblastic leukaemia. Br J Haematol. 2018;181(4):523–7.

    PubMed  CAS  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  13. West GB, Brown JH, Enquist BJ. A general model for the origin of allometric scaling laws in biology. Science. 1997;276(5309):122–6.

    PubMed  CAS  Google Scholar 

  14. Anderson BJ, Holford NHG. Mechanism-based concepts of size and maturity in pharmacokinetics. Annu Rev Pharmacol Toxicol. 2008;48:303–32.

    PubMed  CAS  Google Scholar 

  15. Germovsek E, Barker C, Sharland M, Standing JF. Scaling clearance in paediatric pharmacokinetics: all models are wrong, which are useful? Br J Clin Pharmacol. 2016;83:777–90.

    PubMed  PubMed Central  Google Scholar 

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

    CAS  Google Scholar 

  17. Nguyen T, Mouksassi M-S, Holford N, Al-Huniti N, Freedman I, Hooker A, et al. Model evaluation of continuous data pharmacometric models: metrics and graphics. CPT Pharmacomet Syst Pharmacol. 2017;6:87–109.

    CAS  Google Scholar 

  18. Dosne A-G, Bergstrand M, Karlsson MO. An automated sampling importance resampling procedure for estimating parameter uncertainty. J Pharmacokinet Pharmacodyn. 2017;44:509–20.

    PubMed  PubMed Central  Google Scholar 

  19. Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)—a Perl module for NONMEM related programming. Comput Methods Programs Biomed. 2004;75:85–94.

    PubMed  Google Scholar 

  20. Keizer RJ, van Benten M, Beijnen JH, Schellens JHM, Huitema ADR. Pirana and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed. 2011;101:72–9.

    PubMed  Google Scholar 

  21. Beal S, Boeckmann A, Sheiner L. NONMEM user guides. San Francisco: University of California, San Francisco; 1988.

    Google Scholar 

  22. Team RC. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2009.

    Google Scholar 

  23. Osawa T, Naito T, Kaneko T, Mino Y, Ohnishi K, Yamada H, et al. Blood distribution of bortezomib and its kinetics in multiple myeloma patients. Clin Biochem. 2014;47:54–9.

    PubMed  CAS  Google Scholar 

  24. Moreau P, Karamanesht II, Domnikova N, Kyselyova MY, Vilchevska KV, Doronin VA, et al. Pharmacokinetic, pharmacodynamic and covariate analysis of subcutaneous versus intravenous administration of bortezomib in patients with relapsed multiple myeloma. Clin Pharmacokinet. 2012;51:823–9.

    PubMed  CAS  Google Scholar 

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Acknowledgements

The authors thank the investigators, research staff, and patients for their participation in this study.

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Corresponding author

Correspondence to Julie M. Janssen.

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Funding

This clinical study was supported by the Dutch Foundation Children Cancer-Free (clinical research support) and by Janssen Pharmaceuticals (clinical research support and free drug).

Conflict of interest

A. Baruchel has declared links of interest with Amgen, Celgene, Jazz, Novartis, Servier, and Shire. J. M. Janssen, T. P. C. Dorlo, D. Niewerth, A. J. Wilhelm, C. M. Zwaan, J. H. Beijnen, A. Attarbaschi, F. Fagioli, T. Klingebiel, B. De Moerloose, G. Palumbo, A. von Stackelberg, G. J. L. Kaspers, and A. D. R. Huitema have no conflicts of interest to declare, other than the funding mentioned previously.

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Janssen, J.M., Dorlo, T.P.C., Niewerth, D. et al. A Semi-Mechanistic Population Pharmacokinetic/Pharmacodynamic Model of Bortezomib in Pediatric Patients with Relapsed/Refractory Acute Lymphoblastic Leukemia. Clin Pharmacokinet 59, 207–216 (2020). https://doi.org/10.1007/s40262-019-00803-y

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  • DOI: https://doi.org/10.1007/s40262-019-00803-y

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