Population Pharmacokinetics to Model the Time-Varying Clearance of the PEGylated Asparaginase Oncaspar® in Children with Acute Lymphoblastic Leukemia

  • Gudrun Würthwein
  • Claudia Lanvers-Kaminsky
  • Georg Hempel
  • Silke Gastine
  • Anja Möricke
  • Martin Schrappe
  • Mats O. Karlsson
  • Joachim BoosEmail author
Original Research Article


Background and Objectives

The pharmacokinetics of the polyethylene glycol (PEG)-conjugated asparaginase Oncaspar® are characterized by an increase in elimination over time. The focus of our analysis is the better understanding of this time-dependency.


In paediatric acute lymphoblastic leukemia therapy (AIEOP-BFM ALL 2009), two administrations of Oncaspar® (2500 U/m2 intravenously) in induction phase (14-day interval) and one single administration in reinduction were followed by weekly monitoring of asparaginase activity. Non-linear mixed-effects modeling techniques (NONMEM) were used. Samples indicating immunological inactivation were excluded to describe the pharmacokinetics under standard conditions. Models with time-constant or time-varying clearance (CL) as well as transit compartment models with an increase in CL over a chain of compartments were investigated.


Models with time-constant elimination could not adequately describe 6107 asparaginase activities from 1342 patients. Implementing a time-varying CL improved the fit. Modeling an increase of CL over time after dose (Emax- and Weibull-functions) were superior to models with an increase of CL over time after the first administration. However, a transit compartment model came out to be the best structural model.


The increase in elimination of PEGylated asparaginase appears to be driven by physicochemical processes that are drug-related. The observed hydrolytically in vitro instability of the drug leads to the hypothesis that this increase in CL might be due to an in vivo hydrolysis of the instable ester bond between PEG and the enzyme combined with an increased elimination of the partly de-PEGylated enzyme (Trial registered at, NCT0111744).


Acute Lymphoblastic Leukemia Bayesian Information Criterion Asparaginase Objective Function Value Visual Predictive Check 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We wish to thank Andrea Rüffer, Petra Schulze Westhof, Sandra Schulz for laboratory assistance and Jana Golitsch for documentation and data management.

Compliance with Ethical Standards


Limited research support (for data collection and safety reporting) for the ALL-BFM study center in Kiel (Germany) has been received from medac GmbH, Sigma-Tau, Baxter and Jazz Pharmaceuticals. The pharmacological laboratory at the department of Paediatric Haematology and Oncology at the University Hospital Münster received limited research support for drug monitoring from medac GmbH, Sigma-Tau and Baxter. No sources of funding were used to assist with the preparation of this manuscript.

Conflicts of interest

J Boos served personally as a consultant and participated in advisory as well as in safety boards for the medac GmbH. He received support for travel from Eusa Pharma, Jazz Pharmaceuticals, Baxalta and Shire. For medac GmbH, Eusa Pharma, Jazz Pharmaceuticals, Baxalta, Shire and Sigma-Tau he held invited lectures. In addition, institutional grants in the context of ASNase drug monitoring from more or less all ASNase providers contributed to the therapeutic drug monitoring program, including the medac GmbH, Eusa Pharma, Jazz Pharmaceuticals, Baxalta, Shire, Sigma-Tau (all representing the varying marketing authorization holders of E. coli ASNase, PEG-ASNase and Erwinase). G. Hempel received research grants from the medac GmbH, the former distributor of PEG-ASNase in Germany, for analyzing the pharmacokinetics of different ASNase formulations. C. Lanvers-Kaminsky received consulting fees from ERYTECH. G. Würthwein, S. Gastine, A. Möricke and M. O. Karlsson have no potential conflicts of interest to declare.

Ethical approval

The AIEOP-BFM ALL 2009 trial (EudraCT Number 2007-004270-43) was approved by the competent ethics committees of the national coordinating centers. This trial was registered at with the identifier NCT01117441. 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 the parents or guardians of each patient included in the study.

Supplementary material

13318_2017_410_MOESM1_ESM.docx (462 kb)
Supplementary material 1 (DOCX 462 kb)


  1. 1.
    Asselin BL, Whitin JC, Coppola DJ, Rupp IP, Sallan SE, Cohen HJ. Comparative pharmacokinetic studies of three asparaginase preparations. J Clin Oncol. 1993;11:1780–6.CrossRefPubMedGoogle Scholar
  2. 2.
    Müller HJ, Löning L, Horn A, et al. Pegylated asparaginase (Oncaspar) in children with ALL: drug monitoring in reinduction according to the ALL/NHL-BFM 95 protocols. Br J Haematol. 2000;110:379–84.CrossRefPubMedGoogle Scholar
  3. 3.
    Avramis VI, Sencer S, Periclou AP, et al. A randomized comparison of native Escherichia coli asparaginase and polyethylene glycol conjugated asparaginase for treatment of children with newly diagnosed standard-risk acute lymphoblastic leukemia: a Children’s Cancer Group study. Blood. 2002;99:1986–94.CrossRefPubMedGoogle Scholar
  4. 4.
    Avramis VI, Spence SA. Clinical pharmacology of asparaginases in the United States: asparaginase population pharmacokinetic and pharmacodynamic (PK-PD) models (NONMEM) in adult and pediatric ALL patients. J Pediatr Hematol Oncol. 2007;29:239–47.CrossRefPubMedGoogle Scholar
  5. 5.
    Hempel G, Müller HJ, Lanvers-Kaminsky C, Würthwein G, Hoppe A, Boos J. A population pharmacokinetic model for pegylated-asparaginase in children. Br J Haematol. 2010;148:119–25.CrossRefPubMedGoogle Scholar
  6. 6.
    EMA. Assessment report Oncaspar: EMEA/H/C/003789/0000. 2015. Accessed 06 Mar 2017.
  7. 7.
    van der Sluis Vrooman LM, Pieters R, et al. Consensus expert recommendations for identification and management of asparaginase hypersensitivity and silent inactivation. Haematologica. 2016;101:279–85.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Lanvers C, Vieira Pinheiro JP, Hempel G, Wuerthwein G, Boos J. Analytical validation of a microplate reader-based method for the therapeutic drug monitoring of l-asparaginase in human serum. Anal Biochem. 2002;309:117–26.CrossRefPubMedGoogle Scholar
  9. 9.
    Icon Development Solutions. NONMEM Users’s Guides: Ellicott City; 2009.Google Scholar
  10. 10.
    R Core Team. Vienna, Austria. R: a language and environment for statistical computing: R Foundation for Statistical Computing; 2014.Google Scholar
  11. 11.
    Keizer RJ, Karlsson MO, Hooker A. Modeling and simulation workbench for NONMEM: tutorial on Pirana, PsN, and Xpose. CPT Pharmacometr Syst Pharmacol. 2013;2:e50.CrossRefGoogle Scholar
  12. 12.
    Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Progr Biomed. 2005;79:241–57.CrossRefGoogle Scholar
  13. 13.
    Lindbom L, Ribbing J, Jonsson EN. Perl-speaks-NONMEM (PsN)—a Perl module for NONMEM related programming. Comput Methods Progr Biomed. 2004;75:85–94.CrossRefGoogle Scholar
  14. 14.
    Mosteller RD. Simplified calculation of body-surface area. N Engl J Med. 1987;317:1098.PubMedGoogle Scholar
  15. 15.
    Ahn JE, Karlsson MO, Dunne A, Ludden TM. Likelihood based approaches to handling data below the quantification limit using NONMEM VI. J Pharmacokinet Pharmacodyn. 2008;35:401–21.CrossRefPubMedGoogle Scholar
  16. 16.
    Bergstrand M, Karlsson MO. Handling data below the limit of quantification in mixed effect models. AAPS J. 2009;11:371–80.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Rousseau A, Leger F, Le Meur Y, et al. Population pharmacokinetic modeling of oral cyclosporin using NONMEM: comparison of absorption pharmacokinetic models and design of a Bayesian estimator. Ther Drug Monit. 2004;26:23–30.CrossRefPubMedGoogle Scholar
  18. 18.
    Savic RM, Jonker DM, Kerbusch T, Karlsson MO. Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies. J Pharmacokinet Pharmacodyn. 2007;34:711–26.CrossRefPubMedGoogle Scholar
  19. 19.
    Schwartz G. Estimating the dimension of a model. Ann Stat. 1978;6:461–4.CrossRefGoogle Scholar
  20. 20.
    Hassan M, Svensson US, Ljungman P, et al. A mechanism-based pharmacokinetic-enzyme model for cyclophosphamide autoinduction in breast cancer patients. Br J Clin Pharmacol. 1999;48:669–77.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Raes A, van Aken S, Craen M, Donckerwolcke R, Vande Walle J. A reference frame for blood volume in children and adolescents. BMC Pediatr. 2006;6:3.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    FDA Label information. Oncaspar: label information. 2014. Accessed 03 Mar 2017.
  23. 23.
    Borghorst S, Pieters R, Kuehnel HJ, Boos J, Hempel G. Population pharmacokinetics of native Escherichia coli asparaginase. Pediatr Hematol Oncol. 2012;29:154–65.CrossRefPubMedGoogle Scholar
  24. 24.
    Angiolillo AL, Schore RJ, Devidas M, et al. Pharmacokinetic and pharmacodynamic properties of calaspargase pegol Escherichia coli l-asparaginase in the treatment of patients with acute lymphoblastic leukemia: results from Children’s Oncology Group Study AALL07P4. J Clin Oncol. 2014;32:3874–82.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Paediatric Haematology and OncologyUniversity Hospital MuensterMuensterGermany
  2. 2.Department of Pharmaceutical and Medical Chemistry-Clinical PharmacyMuensterGermany
  3. 3.Department of PediatricsChristian-Albrechts-University Kiel and University Medical Center Schleswig-HolsteinKielGermany
  4. 4.Department of Pharmaceutical BiosciencesUppsala UniversityUppsalaSweden

Personalised recommendations