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

  • M. H. Diekstra
  • , A. Fritsch
  • , F. Kanefendt
  • , J. J. Swen
  • , D. J. A. R. Moes
  • , F. Soergel
  • , M. Kinzig
  • , C. Stelzer
  • , D. Schindele
  • , T. Gauler
  • , S. Hauser
  • , D. Houtsma
  • , M. Roessler
  • , B. Moritz
  • , K. Mross
  • , L. Bergmann
  • , E. Oosterwijk
  • , L. A. Kiemeney
  • , H. J. Guchelaar
  • , U. Jaehde*
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)604-613
Number of pages10
JournalCPT: Pharmacometrics and Systems Pharmacology
Volume6
Issue number9
DOIs
Publication statusPublished - Sept 2017

Keywords

  • RENAL-CELL CARCINOMA
  • ENDOTHELIAL GROWTH-FACTOR
  • SINGLE-NUCLEOTIDE POLYMORPHISMS
  • 1ST-LINE SUNITINIB
  • METABOLITE SU12662
  • HEALTHY-VOLUNTEERS
  • ACTIVE METABOLITE
  • INTERFERON-ALPHA
  • SU11248
  • BIOMARKER

Fingerprint

Dive into the research topics of 'Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib-Treated Cancer'. Together they form a unique fingerprint.

Cite this