DDMODEL00000198: Tumor growth inhibition model for Sunitinib Treatment in GIST

  public model
Short description:
A tumor growth inhibition model for longitudinal tumor size following placebo and sunitinib treatment in GIST patients.
Original code
  • PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST.
  • Hansson EK, Amantea MA, Westwood P, Milligan PA, Houk BE, French J, Karlsson MO, Friberg LE
  • CPT: pharmacometrics & systems pharmacology, 1/2013, Volume 2, pages: e84
  • Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
  • The predictive value of longitudinal biomarker data (vascular endothelial growth factor (VEGF), soluble VEGF receptor (sVEGFR)-2, sVEGFR-3, and soluble stem cell factor receptor (sKIT)) for tumor response and survival was assessed based on data from 303 patients with imatinib-resistant gastrointestinal stromal tumors (GIST) receiving sunitinib and/or placebo treatment. The longitudinal tumor size data were well characterized by a tumor growth inhibition model, which included, as significant descriptors of tumor size change, the model-predicted relative changes from baseline over time for sKIT (most significant) and sVEGFR-3, in addition to sunitinib exposure. Survival time was best described by a parametric time-to-event model with baseline tumor size and relative change in sVEGFR-3 over time as predictive factors. Based on the proposed modeling framework to link longitudinal biomarker data with overall survival using pharmacokinetic-pharmacodynamic models, sVEGFR-3 demonstrated the greatest predictive potential for overall survival following sunitinib treatment in GIST.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e84; doi:10.1038/psp.2013.61; advance online publication 20 November 2013.
Sreenath M Krishnan
Context of model development: Mechanistic Understanding; Variability sources in PK and PD (CYP, Renal, Biomarkers);
Long technical model description: Final PD model (predicting tumour size) of drug and biomarkers during sunitinib treatment of imatinib-resistant GIST. 2 biomarkers from BM included: sVEGFR-3 and sKIT. 4 compartments initiated to BM posthoc baselines at t=0. 1st/2nd compartment: sKIT timecourse with and without drug effect (placebo). 3rd compartment: sVEGFR-3 timecourse. 4th compartment: tumour size timecourse. Normal scale tumour measurements (DV). Tumour timecourse is a growth inhibition model. Linear inhibition effect by AUC (+) and sKIT/sVEGFR-3 (-). Sunitinib AUC=DOSE/CL. Baseline tumour size covariate; residual variability as measure error. Tumour regrowth/resistance with exponential time-dependent function. Covariate: Baseline tumour size observation. IIV on rate constants: growth rate, drug effect and sKIT effect. Residual error (shared variance estimate): Proportional on DV and Proportional on baseline tumour size observation. Estimation method: FOCE with INTERACTION (NO COVARIANCE STEP).;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: Tumor growth inhibition model; PD model predicting tumour size during sunitinib treatment of imatinib-resistant GIST;
Modelling task in scope: estimation; simulation;
Nature of research: Clinical research & Therapeutic use;
Therapeutic/disease area: Oncology;
Annotations are correct.
This model is not certified.
  • Model owner: Sreenath M Krishnan
  • Submitted: Jun 3, 2016 12:55:49 PM
  • Last Modified: Jun 3, 2016 12:55:49 PM
  • Version: 6 public model Download this version
    • Submitted on: Jun 3, 2016 12:55:49 PM
    • Submitted by: Sreenath M Krishnan
    • With comment: Updated model annotations.