Ribba2018 - Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy

  public model
Model Identifier
MODEL1909050002
Short description 
This is a model developed to predict concentrations of cergutuzumab amunaleukin (CEA-IL2v) after various systemic dosing intensities.
Format
SBML (L2V4)
Related Publication
  • Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy.
  • Ribba B, Boetsch C, Nayak T, Grimm HP, Charo J, Evers S, Klein C, Tessier J, Charoin JE, Phipps A, Pisa P, Teichgräber V
  • Clinical cancer research : an official journal of the American Association for Cancer Research , 7/ 2018 , Volume 24 , Issue 14 , pages: 3325-3333 , PubMed ID: 29463551
  • Pharmaceutical Sciences, Roche Pharmaceutical Research & Early Development, Roche Innovation Center, Basel, Switzerland. benjamin.ribba@roche.com.
  • Purpose: Optimal dosing is critical for immunocytokine-based cancer immunotherapy to maximize efficacy and minimize toxicity. Cergutuzumab amunaleukin (CEA-IL2v) is a novel CEA-targeted immunocytokine. We set out to develop a mathematical model to predict intratumoral CEA-IL2v concentrations following various systemic dosing intensities.Experimental Design: Sequential measurements of CEA-IL2v plasma concentrations in 74 patients with solid tumors were applied in a series of differential equations to devise a model that also incorporates the peripheral concentrations of IL2 receptor-positive cell populations (i.e., CD8+, CD4+, NK, and B cells), which affect tumor bioavailability of CEA-IL2v. Imaging data from a subset of 14 patients were subsequently utilized to additionally predict antibody uptake in tumor tissues.Results: We created a pharmacokinetic/pharmacodynamic mathematical model that incorporates the expansion of IL2R-positive target cells at multiple dose levels and different schedules of CEA-IL2v. Model-based prediction of drug levels correlated with the concentration of IL2R-positive cells in the peripheral blood of patients. The pharmacokinetic model was further refined and extended by adding a model of antibody uptake, which is based on drug dose and the biological properties of the tumor. In silico predictions of our model correlated with imaging data and demonstrated that a dose-dense schedule comprising escalating doses and shortened intervals of drug administration can improve intratumoral drug uptake and overcome consumption of CEA-IL2v by the expanding population of IL2R-positive cells.Conclusions: The model presented here allows simulation of individualized treatment plans for optimal dosing and scheduling of immunocytokines for anticancer immunotherapy. Clin Cancer Res; 24(14); 3325-33. ©2018 AACRSee related commentary by Ruiz-Cerdá et al., p. 3236.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer

Metadata information

hasProperty (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Cergutuzumab Amunaleukin

isDescribedBy (1 statement)
Curation status
Non-curated
Modelling approach(es)
ordinary differential equation model
Tags
Immuno-oncology

Connected external resources

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Model files
Ribba2018 Model 2.xml SBML L2V4 Representation of Ribba2018 - Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 27.55 KB Preview | Download

Additional files
Ribba2018 Model 2.cps COPASI file of Ribba2018 - Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy 69.54 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Sep 5, 2019 12:39:41 PM
  • Last Modified: Sep 5, 2019 12:39:41 PM
Revisions
  • Version: 1 public model Download this version
    • Submitted on: Sep 5, 2019 12:39:41 PM
    • Submitted by: Johannes Meyer
    • With comment: Import of Ribba2018 - Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy