Journal of Pharmacokinetics and Pharmacodynamics

, Volume 42, Issue 6, pp 709–720 | Cite as

Pharmacodynamic model for chemoradiotherapy-induced thrombocytopenia in mice

  • Wojciech Krzyzanski
  • Juan Jose Perez-Ruixo
  • John HarroldEmail author
Original Paper


A mechanistic model describing the effects of chemotherapy and radiation on platelet counts and endogenous thrombopoietin (eTPO) in mice was developed. Thrombocytopenia was induced in mice by injection of carboplatin followed by the whole body irradiation on days 0, 28, and 56, with platelet and eTPO samples collected over 84 days. The pharmacodynamic model consisted of a series of aging compartments representing proliferating megakaryocyte precursors, megakaryocytes, and platelets with possible eTPO clearance through internalization. The cytotoxic effects of treatment were described by the kinetics of the effect (K-PD) model, and stimulation of platelet production by eTPO was considered to be driven by receptor occupancy. The proposed PD model adequately described the platelet counts and eTPO concentrations in mice by accounting for nadirs and peaks of platelet count, and rebounds in eTPO time course profiles. The estimates of model parameters were in good agreement with their physiological values reported in literature for mice with platelet lifespan of 4.3 days and 185 cMpl receptors per platelet. The predicted duration of the treatment effect was 0.82 h (approximately 5 carboplatin half-lives in mice). The data was not informative about the eTPO stimulatory effect as the nominal precursor production rate was sufficient to account for platelet response to treatment. The model quantified the inverse relationship between eTPO levels and platelet counts and offered an explanation of the tolerance effect observed in the eTPO data. The simulated rebound in free receptors levels correlated with rebounds in eTPO levels. The model suggests that the duration of the toxic effects is determined by the turnover of the proliferating cells in the bone marrow. This indicates that the lifespan of the target cells (megakaryocyte precursors, megakaryocytes and platelets) is a key determinant in the duration of both drug exposure and toxicity due to treatment. The model can be extended to account for pharmacokinetics of exogenous drugs and be applied to analysis of human data.


Chemoradiation Receptor-mediated disposition Thrombocytopenia Thrombopoietin 



The authors would like to thank Graham Molineux, Ping Wei and Trish McElroy for conducting the experiments to generate the data used in this modeling exercise and Murad Melhem for critical review of the manuscript.

Financial support

This study was sponsored by Amgen Inc., which was involved in the study design, data collection, analysis, interpretation, writing the manuscript, and the decision to submit the manuscript for publication.

Compliance with ethical standards

Potential conflicts of interest

The following authors are employees of and own stock in Amgen Inc.: Juan Jose Perez Ruixo and John Harrold. Wojciech Krzyzanski is a consultant for Amgen and received consultation fees for this work.

Supplementary material

10928_2015_9440_MOESM1_ESM.docx (111 kb)
Supplementary material 1 (DOCX 112 kb)
10928_2015_9440_MOESM2_ESM.ctl (6 kb)
Supplementary material 2 (CTL 7 kb)
10928_2015_9440_MOESM3_ESM.csv (21 kb)
Supplementary material 3 (CSV 22 kb)


  1. 1.
    Kaushansky K, Roth GJ (2004) Megakaryocytes and platelets. Wintrobe’s Clinical HematologyGoogle Scholar
  2. 2.
    Kuter DJ (2009) Thrombopoietin and thrombopoietin mimetics in the treatment of thrombocytopenia. Annu Rev Med 60:193–206CrossRefPubMedGoogle Scholar
  3. 3.
    Salmon SE, Sartorelli AC (2001) Cancer chemotherapy. McGraw-Hill, New YorkGoogle Scholar
  4. 4.
    Woo S, Krzyzanski W, Jusko WJ (2008) Pharmacodynamic model for chemotherapy-induced anemia in rats. Cancer Chemother Pharmacol 62:123–133. doi: 10.1007/s00280-007-0582-9 PubMedCentralCrossRefPubMedGoogle Scholar
  5. 5.
    Bernstein SH, Jusko WJ, Krzyzanski W, Nichol J, Wetzler M (2002) Pharmacodynamic modeling of thrombopoietin, platelet, and megakaryocyte dynamics in patients with acute myeloid leukemia undergoing dose intensive chemotherapy. J Clin Pharmacol 42:501–511CrossRefPubMedGoogle Scholar
  6. 6.
    Testart-Paillet D, Girard P, You B, Freyer G, Pobel C, Tranchand B (2007) Contribution of modelling chemotherapy-induced hematological toxicity for clinical practice. Crit Rev Oncol Hematol 63:1–11. doi: 10.1016/j.critrevonc.2007.01.005 CrossRefPubMedGoogle Scholar
  7. 7.
    Friberg LE, Henningsson A, Maas H, Nguyen L, Karlsson MO (2002) Model of chemotherapy-induced myelosuppression with parameter consistency across drugs. J Clin Oncol 20:4713–4721. doi: 10.1200/JCO.2002.02.140 CrossRefPubMedGoogle Scholar
  8. 8.
    Friberg LE, Freijs A, Sandström M, Karlsson MO (2000) Semiphysiological model for the time course of leukocytes after varying schedules of 5-fluorouracil in rats. J Pharmacol Exp Ther 295:734–740PubMedGoogle Scholar
  9. 9.
    Bender BC, Schaedeli-Stark F, Koch R, Joshi A, Chu Y-W, Rugo H, Krop IE, Girish S, Friberg LE, Gupta M (2012) A population pharmacokinetic/pharmacodynamic model of thrombocytopenia characterizing the effect of trastuzumab emtansine (T-DM1) on platelet counts in patients with HER2-positive metastatic breast cancer. Cancer Chemother Pharmacol 70:591–601. doi: 10.1007/s00280-012-1934-7 CrossRefPubMedGoogle Scholar
  10. 10.
    du Rieu QC, Fouliard S, Jacquet-Bescond A, Robert R, Kloos I, Depil S, Chatelut E, Chenel M (2013) Application of hematological toxicity modeling in clinical development of abexinostat (S-78454, PCI-24781), a new histone deacetylase inhibitor. Pharm Res 30:2640–2653. doi: 10.1007/s11095-013-1089-1 CrossRefGoogle Scholar
  11. 11.
    Kobuchi S, Ito Y, Hayakawa T, Nishimura A, Shibata N, Takada K, Sakaeda T (2015) Semi-physiological pharmacokinetic-pharmacodynamic (PK-PD) modeling and simulation of 5-fluorouracil for thrombocytopenia in rats. Xenobiotica 45:19–28. doi: 10.3109/00498254.2014.943335 CrossRefPubMedGoogle Scholar
  12. 12.
    Perez-Ruixo JJ, Green B, Doshi S, Wang Y-M, Mould DR (2012) Romiplostim dose response in patients with immune thrombocytopenia. J Clin Pharmacol 52:1540–1551. doi: 10.1177/0091270011420843 CrossRefPubMedGoogle Scholar
  13. 13.
    Perez-Ruixo JJ, Doshi S, Wang Y-MC, Mould DR (2013) Romiplostim dose-response in patients with myelodysplastic syndromes. Br J Clin Pharmacol 75:1445–1454. doi: 10.1111/bcp.12041 PubMedCentralCrossRefPubMedGoogle Scholar
  14. 14.
    Hayes S, Mudd PN, Ouellet D, Johnson BM, Williams D, Gibiansky E (2013) Population PK/PD modeling of eltrombopag in subjects with advanced solid tumors with chemotherapy-induced thrombocytopenia. Cancer Chemother Pharmacol 71:1507–1520. doi: 10.1007/s00280-013-2150-9 CrossRefPubMedGoogle Scholar
  15. 15.
    Friberg LE, Karlsson MO (2003) Mechanistic models for myelosuppression. Invest New Drugs. doi: 10.1023/A:1023573429626 PubMedGoogle Scholar
  16. 16.
    Li J, Xia Y, Kuter DJ (1999) Interaction of thrombopoietin with the platelet c-mpl receptor in plasma: binding, internalization, stability and pharmacokinetics. Br J Haematol. 106:345–356. doi: 10.1046/j.1365-2141.1999.01571.x CrossRefPubMedGoogle Scholar
  17. 17.
    Mager DE, Krzyzanski W (2005) Quasi-equilibrium pharmacokinetic model for drugs exhibiting target-mediated drug disposition. Pharm Res 22:1589–1596. doi: 10.1007/s11095-005-6650-0 CrossRefPubMedGoogle Scholar
  18. 18.
    Krzyzanski W, Sutjandra L, Perez-Ruixo JJ, Sloey B, Chow AT, Wang Y-M (2012) Pharmacokinetic and pharmacodynamic modeling of romiplostim in animals. Pharm Res 30:655–669. doi: 10.1007/s11095-012-0894-2 CrossRefPubMedGoogle Scholar
  19. 19.
    Jacqmin P, Snoeck E, van Schaick EA, Gieschke R, Pillai P, Steimer JL, Girard P (2007) Modelling response time profiles in the absence of drug concentrations: definition and performance evaluation of the K-PD model. J Pharmacokinet Pharmacodyn 34:57–85. doi: 10.1007/s10928-006-9035-z CrossRefPubMedGoogle Scholar
  20. 20.
    Debili N, Wendling F, Cosman D, Titeux M, Florindo C, Dusanter-Fourt I, Schooley K, Methia N, Charon M, Nador R (1995) The Mpl receptor is expressed in the megakaryocytic lineage from late progenitors to platelets. Blood 85:391–401PubMedGoogle Scholar
  21. 21.
    Vadhan-Raj S, Murray LJ, Bueso-Ramos C, Patel S, Reddy SP, Hoots WK, Johnston T, Papadopolous NE, Hittelman WN, Johnston DA, Yang TA, Paton VE, Cohen RL, Hellmann SD, Benjamin RS, Broxmeyer HE (1997) Stimulation of megakaryocyte and platelet production by a single dose of recombinant human thrombopoietin in patients with cancer. Ann Intern Med 126:673–681CrossRefPubMedGoogle Scholar
  22. 22.
    Yang C, Li YC, Kuter DJ (1999) The physiological response of thrombopoietin (c-Mpl ligand) to thrombocytopenia in the rat. Br J Haematol. 105:478–485CrossRefPubMedGoogle Scholar
  23. 23.
    Long MW, Gragowski LL, Heffner CH, Boxer LA (1985) Phorbol diesters stimulate the development of an early murine progenitor cell. The burst-forming unit-megakaryocyte. J Clin Invest 76:431–438. doi: 10.1172/JCI111990 PubMedCentralCrossRefPubMedGoogle Scholar
  24. 24.
    Odell TT, Jackson CW (1971) Length of maturation time. In: Paulus JE (ed) Platelet kinetics, radioisotopic, cytological, mathematical, and clinical aspects. North Holland Publishing Company, AmsterdamGoogle Scholar
  25. 25.
    Odell TT, McDONALD TP (1961) Life span of mouse blood platelets. Proc Soc Exp Biol Med 106:107–108CrossRefPubMedGoogle Scholar
  26. 26.
    Wang Y-MC, Krzyzanski W, Doshi S, Xiao JJ, Perez-Ruixo JJ, Chow AT (2010) Pharmacodynamics-mediated drug disposition (PDMDD) and precursor pool lifespan model for single dose of romiplostim in healthy subjects. AAPS J 12:729–740. doi: 10.1208/s12248-010-9234-9 PubMedCentralCrossRefPubMedGoogle Scholar
  27. 27.
    Krzyzanski W, Jusko WJ (2002) Multiple-pool cell lifespan model of hematologic effects of anticancer agents. J Pharmacokinet Pharmacodyn 29:311–337CrossRefPubMedGoogle Scholar
  28. 28.
    Valeriote F, van Putten L (1975) Proliferation-dependent cytotoxicity of anticancer agents: a review. Cancer Res 35:2619–2630PubMedGoogle Scholar
  29. 29.
    Fernandes DJ, Sur P, Kute TE, Capizzi RL (1988) Proliferation-dependent cytotoxicity of methotrexate in murine L5178Y leukemia. Cancer Res 48:5638–5644PubMedGoogle Scholar
  30. 30.
    Gabrielsson J, Jusko WJ, Alari L (2000) Modeling of dose-response-time data: four examples of estimating the turnover parameters and generating kinetic functions from response profiles. Biopharm Drug Dispos 21:41–52. doi: 10.1002/1099-081X(200003)21:2<41:AID-BDD217>3.0.CO;2-D CrossRefPubMedGoogle Scholar
  31. 31.
    van Hennik MB, van der Vijgh WJF, Klein I, Elferink F, Vermorken JB, Winograd B, Pinedo HM (1987) Comparative pharmacokinetics of cisplatin and three analogues in mice and humans. Cancer Res. 47:6297–6301PubMedGoogle Scholar
  32. 32.
    Simeoni M, Magni P, Cammia C, De Nicolao G, Croci V, Pesenti E, Germani M, Poggesi I, Rocchetti M (2004) Predictive pharmacokinetic-pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 64:1094–1101CrossRefPubMedGoogle Scholar
  33. 33.
    Tamura H, Ogata K, Luo S, Nakamura K, Yokose N, Dan K, Tohyama K, Yoshida Y, Hamaguchi H, Sakamaki H, Kuwaki T, Tahara T, Kato T, Nomura T (1998) Plasma thrombopoietin (TPO) levels and expression of TPO receptor on platelets in patients with myelodysplastic syndromes. Br J Haematol. 103:778–784CrossRefPubMedGoogle Scholar
  34. 34.
    Yoon SY, Li CY, Tefferi A (2000) Megakaryocyte c-Mpl expression in chronic myeloproliferative disorders and the myelodysplastic syndrome: immunoperoxidase staining patterns and clinical correlates. Eur J Haematol 65:170–174CrossRefPubMedGoogle Scholar
  35. 35.
    Pastor ML, Laffont CM, Gladieff L, Schmitt A, Chatelut E, Concordet D (2013) Model-based approach to describe G-CSF effects in carboplatin-treated cancer patients. Pharm Res 30:2795–2807. doi: 10.1007/s11095-013-1099-z CrossRefPubMedGoogle Scholar
  36. 36.
    Quartino AL, Karlsson MO, Lindman H, Friberg LE (2014) Characterization of endogenous G-CSF and the inverse correlation to chemotherapy-induced neutropenia in patients with breast cancer using population modeling. Phram Res 31:3390–3403. doi: 10.1007/s11095-014-1429-9 CrossRefGoogle Scholar
  37. 37.
    Gaddum JH, Hameed KA, Hathway DE, Stephens FF (1955) Quantitative studies of antagonists for 5-hydroxytryptamine. Q J Exp Physiol Cogn Med Sci 40:49–74. doi: 10.1113/expphysiol.1955.sp001097 PubMedGoogle Scholar
  38. 38.
    Yan X, Chen Y, Krzyzanski W (2012) Methods of solving rapid binding target-mediated drug disposition model for two drugs competing for the same receptor. J Pharmacokinet Pharmacodyn 39:543–560. doi: 10.1007/s10928-012-9267-z PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Wojciech Krzyzanski
    • 1
  • Juan Jose Perez-Ruixo
    • 2
  • John Harrold
    • 2
    Email author
  1. 1.Department of Pharmaceutical SciencesUniversity at BuffaloBuffaloUSA
  2. 2.Clinical Pharmacology, Modeling and SimulationAmgen Inc.Thousand OaksUSA

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