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CPT Pharmacometrics Syst Pharmacol. 2017 Sep;6(9):604-613. doi: 10.1002/psp4.12210. Epub 2017 Jul 13.

Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib-Treated Cancer.

Author information

1
Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands.
2
Institute of Pharmacy, Clinical Pharmacy, University of Bonn, Bonn, Germany.
3
IBMP - Institute for Biomedical and Pharmaceutical Research, Nürnberg-Heroldsberg, Germany.
4
Department for Urology and Paediatric Urology, University of Magdeburg, Magdeburg, Germany.
5
West German Cancer Center, University Hospital Essen, Essen, Germany.
6
Department of Urology, University Hospital Bonn, Bonn, Germany.
7
Haga Hospital, Den Haag, The Netherlands.
8
CESAR Central Office, Vienna, Austria.
9
Department of Medical Oncology, Tumor Biology Center Freiburg, Freiburg, Germany.
10
Cancer-Center Rhein-Main, University Hospital Frankfurt, Frankfurt, Germany.
11
Department of Urology, Radboud University Nijmegen, Nijmegen, The Netherlands.
12
Department of Epidemiology and Biostatistics, Radboud University Nijmegen, Nijmegen, The Netherlands.

Abstract

The tyrosine kinase inhibitor sunitinib is used as first-line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed-dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR-2 and sVEGFR-3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C-II-005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time-to-event (TTE) models. Baseline sVEGFR-2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD-guided strategies for the individualization of anti-angiogenic therapies.

PMID:
28571114
PMCID:
PMC5613186
DOI:
10.1002/psp4.12210
[Indexed for MEDLINE]
Free PMC Article

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