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Published in: Clinical Pharmacokinetics 3/2017

01-03-2017 | Original Research Article

Development of a Pharmacokinetic Model to Describe the Complex Pharmacokinetics of Pazopanib in Cancer Patients

Authors: Huixin Yu, Nielka van Erp, Sander Bins, Ron H. J. Mathijssen, Jan H. M. Schellens, Jos H. Beijnen, Neeltje Steeghs, Alwin D. R. Huitema

Published in: Clinical Pharmacokinetics | Issue 3/2017

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Abstract

Background and Objective

Pazopanib is a multi-targeted anticancer tyrosine kinase inhibitor. This study was conducted to develop a population pharmacokinetic (popPK) model describing the complex pharmacokinetics of pazopanib in cancer patients.

Methods

Pharmacokinetic data were available from 96 patients from three clinical studies. A multi-compartment model including (i) a complex absorption profile, (ii) the potential non-linear dose–concentration relationship and (iii) the potential long-term decrease in exposure was developed.

Results

A two-compartment model best described pazopanib pharmacokinetics. The absorption phase was modelled by two first-order processes: 36 % (relative standard error [RSE] 34 %) of the administered dose was absorbed with a relatively fast rate (0.4 h−1 [RSE 31 %]); after a lag time of 1.0 h (RSE 6 %), the remaining dose was absorbed at a slower rate (0.1 h−1 [RSE 28 %]). The relative bioavailability (rF) at a dose of 200 mg was fixed to 1. With an increasing dose, the rF was strongly reduced, which was modelled with an E max (maximum effect) model (E max was fixed to 1, the dose at half of maximum effect was estimated as 480 mg [RSE 23 %]). Interestingly, the plasma exposure to pazopanib also decreased over time, modelled on rF with a maximum magnitude of 50 % (RSE 27 %) and a first-order decay constant of 0.15 day−1 (RSE 43 %). The inter-patient and intra-patient variability on rF were estimated as 36 % (RSE 16 %) and 75 % (RSE 22 %), respectively.

Conclusion

A popPK model for pazopanib was developed that illustrated the complex absorption process, the non-linear dose–concentration relationship, the high inter-patient and intra-patient variability, and the first-order decay of pazopanib concentration over time. The developed popPK model can be used in clinical practice to screen covariates and guide therapeutic drug monitoring.
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Literature
3.
go back to reference van Leeuwen RWF, van Gelder T, Mathijssen RHJ, Jansman FGA. Drug–drug interactions with tyrosine-kinase inhibitors: a clinical perspective. Lancet Oncol. 2014;15(8):e315–26.CrossRefPubMed van Leeuwen RWF, van Gelder T, Mathijssen RHJ, Jansman FGA. Drug–drug interactions with tyrosine-kinase inhibitors: a clinical perspective. Lancet Oncol. 2014;15(8):e315–26.CrossRefPubMed
4.
go back to reference Hurwitz HI, Dowlati A, Saini S, Savage S, Suttle AB, Gibson DM, et al. Phase I trial of pazopanib in patients with advanced cancer. Clin Cancer Res. 2009;15(12):4220–7.CrossRefPubMed Hurwitz HI, Dowlati A, Saini S, Savage S, Suttle AB, Gibson DM, et al. Phase I trial of pazopanib in patients with advanced cancer. Clin Cancer Res. 2009;15(12):4220–7.CrossRefPubMed
5.
go back to reference de Wit D, van Erp NP, den Hartigh J, Wolterbeek R, den Hollander-van Deursen M, Labots M, et al. Therapeutic drug monitoring to individualize the dosing of pazopanib: a pharmacokinetic feasibility study. Ther Drug Monit. 2014;37(3):331–8.CrossRef de Wit D, van Erp NP, den Hartigh J, Wolterbeek R, den Hollander-van Deursen M, Labots M, et al. Therapeutic drug monitoring to individualize the dosing of pazopanib: a pharmacokinetic feasibility study. Ther Drug Monit. 2014;37(3):331–8.CrossRef
6.
go back to reference Suttle AB, Ball HA, Molimard M, Hutson TE, Carpenter C, Rajagopalan D, et al. Relationships between pazopanib exposure and clinical safety and efficacy in patients with advanced renal cell carcinoma. Br J Cancer. 2014;111(10):1909–16.CrossRefPubMedPubMedCentral Suttle AB, Ball HA, Molimard M, Hutson TE, Carpenter C, Rajagopalan D, et al. Relationships between pazopanib exposure and clinical safety and efficacy in patients with advanced renal cell carcinoma. Br J Cancer. 2014;111(10):1909–16.CrossRefPubMedPubMedCentral
7.
go back to reference Yu H, Steeghs N, Nijenhuis CM, Schellens JHM, Beijnen JH, Huitema ADR. Practical guidelines for therapeutic drug monitoring of anticancer tyrosine kinase inhibitors: focus on the pharmacokinetic targets. Clin Pharmacokinet. 2014;53(4):305–25.CrossRefPubMed Yu H, Steeghs N, Nijenhuis CM, Schellens JHM, Beijnen JH, Huitema ADR. Practical guidelines for therapeutic drug monitoring of anticancer tyrosine kinase inhibitors: focus on the pharmacokinetic targets. Clin Pharmacokinet. 2014;53(4):305–25.CrossRefPubMed
8.
go back to reference Yu H, Steeghs N, Kloth JSL, de Wit D, van Hasselt JGC, van Erp NP, et al. Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662. Br J Clin Pharmacol. 2015;79(5):809–19.CrossRefPubMedPubMedCentral Yu H, Steeghs N, Kloth JSL, de Wit D, van Hasselt JGC, van Erp NP, et al. Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662. Br J Clin Pharmacol. 2015;79(5):809–19.CrossRefPubMedPubMedCentral
9.
go back to reference Kerbusch T, Huitema ADR, Ouwerkerk J, Keizer HJ, Mathôt RA, Schellens JHM, et al. Evaluation of the autoinduction of ifosfamide metabolism by a population pharmacokinetic approach using NONMEM. Br J Clin Pharmacol. 2000;49(6):555–61.CrossRefPubMedPubMedCentral Kerbusch T, Huitema ADR, Ouwerkerk J, Keizer HJ, Mathôt RA, Schellens JHM, et al. Evaluation of the autoinduction of ifosfamide metabolism by a population pharmacokinetic approach using NONMEM. Br J Clin Pharmacol. 2000;49(6):555–61.CrossRefPubMedPubMedCentral
10.
go back to reference Kloth JSL, Klümpen H-J, Yu H, Eechoute K, Samer CF, Kam BLR, et al. Predictive value of CYP3A and ABCB1 phenotyping probes for the pharmacokinetics of sunitinib: the ClearSun study. Clin Pharmacokinet. 2014;53(3):261–9.CrossRefPubMed Kloth JSL, Klümpen H-J, Yu H, Eechoute K, Samer CF, Kam BLR, et al. Predictive value of CYP3A and ABCB1 phenotyping probes for the pharmacokinetics of sunitinib: the ClearSun study. Clin Pharmacokinet. 2014;53(3):261–9.CrossRefPubMed
11.
go back to reference Diekstra MHM, Klümpen HJ, Lolkema MPJK, Yu H, Kloth JSL, Gelderblom H, et al. Association analysis of genetic polymorphisms in genes related to sunitinib pharmacokinetics, specifically clearance of sunitinib and SU12662. Clin Pharmacol Ther. 2014;96(1):81–9.CrossRefPubMed Diekstra MHM, Klümpen HJ, Lolkema MPJK, Yu H, Kloth JSL, Gelderblom H, et al. Association analysis of genetic polymorphisms in genes related to sunitinib pharmacokinetics, specifically clearance of sunitinib and SU12662. Clin Pharmacol Ther. 2014;96(1):81–9.CrossRefPubMed
12.
go back to reference Gotta V, Widmer N, Montemurro M, Leyvraz S, Haouala A, Decosterd LA, et al. Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels. Clin Pharmacokinet. 2012;51(3):187–201.CrossRefPubMed Gotta V, Widmer N, Montemurro M, Leyvraz S, Haouala A, Decosterd LA, et al. Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels. Clin Pharmacokinet. 2012;51(3):187–201.CrossRefPubMed
13.
go back to reference Hamberg P, Mathijssen RHJ, de Bruijn P, Leonowens C, van der Biessen D, Eskens FA, et al. Impact of pazopanib on docetaxel exposure: results of a phase I combination study with two different docetaxel schedules. Cancer Chemother Pharmacol. 2014;75(2):365–71.CrossRefPubMed Hamberg P, Mathijssen RHJ, de Bruijn P, Leonowens C, van der Biessen D, Eskens FA, et al. Impact of pazopanib on docetaxel exposure: results of a phase I combination study with two different docetaxel schedules. Cancer Chemother Pharmacol. 2014;75(2):365–71.CrossRefPubMed
14.
go back to reference Hamberg P, Boers-Sonderen MJ, van der Graaf WTA, de Bruijn P, Suttle AB, Eskens FALM, et al. Pazopanib exposure decreases as a result of an ifosfamide-dependent drug-drug interaction: results of a phase I study. Br J Cancer. 2014;110(4):888–93.CrossRefPubMed Hamberg P, Boers-Sonderen MJ, van der Graaf WTA, de Bruijn P, Suttle AB, Eskens FALM, et al. Pazopanib exposure decreases as a result of an ifosfamide-dependent drug-drug interaction: results of a phase I study. Br J Cancer. 2014;110(4):888–93.CrossRefPubMed
15.
go back to reference Imbs D-C, Négrier S, Cassier P, Hollebecque A, Varga A, Blanc E, et al. Pharmacokinetics of pazopanib administered in combination with bevacizumab. Cancer Chemother Pharmacol. 2014;73(6):1189–96.CrossRefPubMed Imbs D-C, Négrier S, Cassier P, Hollebecque A, Varga A, Blanc E, et al. Pharmacokinetics of pazopanib administered in combination with bevacizumab. Cancer Chemother Pharmacol. 2014;73(6):1189–96.CrossRefPubMed
16.
go back to reference Zhang L, Beal SL, Sheiner LB. Simultaneous vs. sequential analysis for population PK/PD data I: best-case performance. J Pharmacokinet Pharmacodyn. 2003;30(6):387–404.CrossRefPubMed Zhang L, Beal SL, Sheiner LB. Simultaneous vs. sequential analysis for population PK/PD data I: best-case performance. J Pharmacokinet Pharmacodyn. 2003;30(6):387–404.CrossRefPubMed
17.
go back to reference Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011;13(2):143–51.CrossRefPubMedPubMedCentral Bergstrand M, Hooker AC, Wallin JE, Karlsson MO. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 2011;13(2):143–51.CrossRefPubMedPubMedCentral
18.
go back to reference Beal SL, Boeckman AJ, Sheiner LB, editors. NONMEM user guides. San Francisco: University of Califomia at San Francisco; 1988. Beal SL, Boeckman AJ, Sheiner LB, editors. NONMEM user guides. San Francisco: University of Califomia at San Francisco; 1988.
19.
go back to reference Lindbom L, Pihlgren P, Jonsson EN, Jonsson N. PsN-Toolkit–a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005;79(3):241–57.CrossRefPubMed Lindbom L, Pihlgren P, Jonsson EN, Jonsson N. PsN-Toolkit–a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005;79(3):241–57.CrossRefPubMed
20.
go back to reference Keizer RJ, van Benten M, Beijnen JH, Schellens JHM, Huitema ADR. Piraña and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed. 2011;101(1):72–9.CrossRefPubMed Keizer RJ, van Benten M, Beijnen JH, Schellens JHM, Huitema ADR. Piraña and PCluster: a modeling environment and cluster infrastructure for NONMEM. Comput Methods Programs Biomed. 2011;101(1):72–9.CrossRefPubMed
21.
go back to reference R Development Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2008. R Development Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2008.
22.
go back to reference Jonsson EN, Karlsson MO. Xpose–an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. Comput Methods Programs Biomed. 1999;58(1):51–64.CrossRefPubMed Jonsson EN, Karlsson MO. Xpose–an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. Comput Methods Programs Biomed. 1999;58(1):51–64.CrossRefPubMed
24.
go back to reference Rowland M, Tozer TN. Chapter 7: absorption. Clinical pharmacokinetics and pharmacodynamics, 4th ed. Baltimore: Lippincott Williams & Wilkins; 2011. pp. 183–216. Rowland M, Tozer TN. Chapter 7: absorption. Clinical pharmacokinetics and pharmacodynamics, 4th ed. Baltimore: Lippincott Williams & Wilkins; 2011. pp. 183–216.
25.
go back to reference Imbs D-C, Diéras V, Bachelot T, Campone M, Isambert N, Joly F, et al. Pharmacokinetic interaction between pazopanib and cisplatin regimen. Cancer Chemother Pharmacol. 2016;77(2):385–92.CrossRefPubMed Imbs D-C, Diéras V, Bachelot T, Campone M, Isambert N, Joly F, et al. Pharmacokinetic interaction between pazopanib and cisplatin regimen. Cancer Chemother Pharmacol. 2016;77(2):385–92.CrossRefPubMed
26.
go back to reference Eechoute K, Fransson MN, Reyners AK, De Jong FA, Sparreboom A, Van Der Graaf WTA, et al. A long-term prospective population pharmacokinetic study on imatinib plasma concentrations in GIST patients. Clin Cancer Res. 2012;18(20):5780–7.CrossRefPubMed Eechoute K, Fransson MN, Reyners AK, De Jong FA, Sparreboom A, Van Der Graaf WTA, et al. A long-term prospective population pharmacokinetic study on imatinib plasma concentrations in GIST patients. Clin Cancer Res. 2012;18(20):5780–7.CrossRefPubMed
27.
go back to reference Arrondeau J, Mir O, Boudou-Rouquette P, Coriat R, Ropert S, Dumas G, et al. Sorafenib exposure decreases over time in patients with hepatocellular carcinoma. Invest New Drugs. 2012;30(5):2046–9.CrossRefPubMed Arrondeau J, Mir O, Boudou-Rouquette P, Coriat R, Ropert S, Dumas G, et al. Sorafenib exposure decreases over time in patients with hepatocellular carcinoma. Invest New Drugs. 2012;30(5):2046–9.CrossRefPubMed
28.
go back to reference Goh BC, Reddy NJ, Dandamudi UB, Laubscher KH, Peckham T, Hodge JP, et al. An evaluation of the drug interaction potential of pazopanib, an oral vascular endothelial growth factor receptor tyrosine kinase inhibitor, using a modified Cooperstown 5 + 1 cocktail in patients with advanced solid tumors. Clin Pharmacol Ther. 2010;88(5):652–9.CrossRefPubMed Goh BC, Reddy NJ, Dandamudi UB, Laubscher KH, Peckham T, Hodge JP, et al. An evaluation of the drug interaction potential of pazopanib, an oral vascular endothelial growth factor receptor tyrosine kinase inhibitor, using a modified Cooperstown 5 + 1 cocktail in patients with advanced solid tumors. Clin Pharmacol Ther. 2010;88(5):652–9.CrossRefPubMed
30.
go back to reference Verheijen RB, Bins S, Mathijssen RH, Lolkema M, van Doorn L, Schellens JH, et al. Individualized pazopanib dosing: a prospective feasibility study in cancer patients. Clin Cancer Res. 2016. [Epub ahead of print] Verheijen RB, Bins S, Mathijssen RH, Lolkema M, van Doorn L, Schellens JH, et al. Individualized pazopanib dosing: a prospective feasibility study in cancer patients. Clin Cancer Res. 2016. [Epub ahead of print]
31.
go back to reference Ahn JE, Birnbaum AK, Brundage RC. Inherent correlation between dose and clearance in therapeutic drug monitoring settings: possible misinterpretation in population pharmacokinetic analyses. J Pharmacokinet Pharmacodyn. 2005;32(5–6):703–18.CrossRefPubMed Ahn JE, Birnbaum AK, Brundage RC. Inherent correlation between dose and clearance in therapeutic drug monitoring settings: possible misinterpretation in population pharmacokinetic analyses. J Pharmacokinet Pharmacodyn. 2005;32(5–6):703–18.CrossRefPubMed
Metadata
Title
Development of a Pharmacokinetic Model to Describe the Complex Pharmacokinetics of Pazopanib in Cancer Patients
Authors
Huixin Yu
Nielka van Erp
Sander Bins
Ron H. J. Mathijssen
Jan H. M. Schellens
Jos H. Beijnen
Neeltje Steeghs
Alwin D. R. Huitema
Publication date
01-03-2017
Publisher
Springer International Publishing
Published in
Clinical Pharmacokinetics / Issue 3/2017
Print ISSN: 0312-5963
Electronic ISSN: 1179-1926
DOI
https://doi.org/10.1007/s40262-016-0443-y

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