DDMODEL00000192: Lestini_2015_PKPD_Oncology

  public model
Short description:
The model was developed for the inhibition of a biomarker in oncology. The PK was modelled by a one-compartment first-order absorption model. The PD used in the modelling is the relative inhibition of the biomarker.
Original code
  • Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology.
  • Lestini G, Dumont C, Mentré F
  • Pharmaceutical research, 10/2015, Volume 32, Issue 10, pages: 3159-3169
  • IAME, UMR 1137, INSERM, Université Paris Diderot, Sorbonne Paris Cité, F-75018, Paris, France. giulia.lestini@inserm.fr.
  • In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e., when no adaptation is performed, using wrong prior parameters.We evaluated two one-stage designs, ?0 and ?*, optimised for prior and true population parameters, ?0 and ?*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ?0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from ?*.Estimation results of two-stage ADs and ? * were close and much better than those obtained with ? 0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three- and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design.Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement.
Giulia Lestini
Context of model development: Study Design Optimization;
Discrepancy between implemented model and original publication: No discrepancy;
Long technical model description: The PK is modelled by a one compartment first order absorption model. The inhibition of TGFbeta signalling by the treatment is represented by a turnover model, that is a simplification of the semi-mechanistic model developed by Bueno et al.;
Model compliance with original publication: Yes;
Model implementation requiring submitter’s additional knowledge: No;
Modelling context description: PKPD model developed for a small molecule TGFbeta inhibitor.;
Modelling task in scope: optimisation;
Nature of research: Early clinical development (Phases I and II);
Therapeutic/disease area: Oncology;
Annotations are correct.
This model is not certified.
  • Model owner: Giulia Lestini
  • Submitted: Oct 27, 2016 10:36:54 AM
  • Last Modified: Oct 27, 2016 10:36:54 AM
  • Version: 44 public model Download this version
    • Submitted on: Oct 27, 2016 10:36:54 AM
    • Submitted by: Giulia Lestini
    • With comment: Edited model metadata online.