Ontah2019 - Dynamic analysis of a tumor treatment model using oncolytic virus and chemotherapy with saturated infection rate

  public model
Model Identifier
BIOMD0000000877
Short description 
This is a mathematical model describing the treatment of tumors using oncolytic virus and chemotherapy. The model is comprised of nonlinear ordinary differential equations describing the interactions between uninfected tumor cells, infected tumor cells, an oncolytic virus, and chemotherapy.
Format
SBML (L2V4)
Related Publication
  • Dynamic analysis of a tumor treatment model using oncolytic virus and chemotherapy with saturated infection rate
  • Ontah, G.M., Trisilowati, Darti, I.
  • IOP Conference Series: Materials Science and Engineering , 7/ 2019 , Volume 546 , Issue 3 , DOI: 10.1088/1757-899X/546/3/032025
  • Department of Mathematics, Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, 65145, Indonesia
  • Virotherapy is one of the most promising therapies in the treatment of tumors which may be further combined with chemotherapy to accelerate the healing rate. In this article, we propose a mathematical model for the treatment of tumors using oncolytic virus and chemotherapy. This model takes the form of nonlinear ordinary differential equations describing the interactions between uninfected tumor cells, infected tumor cells, an oncolytic virus, and chemotherapy. It is assumed that the rate of infection between uninfected tumor cells and infected tumor cells is in a saturated form. The saturation effect takes into account the fact that the number of contacts between them reaches the maximum value when the immune system works to stop the virus. The dynamical analysis, which includes the existence of equilibrium points, and its stability analysis is investigated. The analysis result shows that the system has three equilibrium points: tumor-free equilibrium point, virus-free equilibrium point and endemic equilibrium point. It is proven that these equilibrium points are conditionally stable. The numerical simulations show the successful combination of chemotherapy and virotherapy using an oncolytic virus in eliminating the tumor cells.
Contributors
Submitter of the first revision: Johannes Meyer
Submitter of this revision: Johannes Meyer
Modellers: Johannes Meyer

Metadata information

hasTaxon (1 statement)
Taxonomy Homo sapiens

hasProperty (3 statements)
Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags
Immuno-oncology

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files
Ontah2019.xml SBML L2V4 Representation of Ontah2019 - Dynamic analysis of a tumor treatment model using oncolytic virus and chemotherapy with saturated infection rate 38.29 KB Preview | Download

Additional files
Ontah2019.cps COPASI file of Ontah2019 - Dynamic analysis of a tumor treatment model using oncolytic virus and chemotherapy with saturated infection rate 73.47 KB Preview | Download
Ontah2019.sedml SED-ML file of Ontah2019 - Dynamic analysis of a tumor treatment model using oncolytic virus and chemotherapy with saturated infection rate 3.16 KB Preview | Download

  • Model originally submitted by : Johannes Meyer
  • Submitted: Nov 27, 2019 4:14:24 PM
  • Last Modified: Nov 27, 2019 4:14:24 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Nov 27, 2019 4:14:24 PM
    • Submitted by: Johannes Meyer
    • With comment: Automatically added model identifier BIOMD0000000877
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
V

Oncolytic Virus 		10.0 item
C

C15681 		30.0 item
I

infected cell ; neoplastic cell 		10.0 item
U

neoplastic cell 		100.0 item
Reactions
Reactions Rate Parameters
=> V; I compartment*b*delta*I delta = 0.5; b = 0.5
V => compartment*gamma*V gamma = 0.1
U + V => I compartment*beta*U*V/(U+I+alpha) beta = 0.01; alpha = 0.5
C => compartment*psi*C psi = 4.17
I => compartment*delta*I delta = 0.5
=> C compartment*mu mu = 150.0
U => ; C compartment*delta_u*U*C/(K_c+C) delta_u = 50.0; K_c = 10000.0
I => ; C compartment*delta_i*I*C/(K_c+C) K_c = 10000.0; delta_i = 60.0
Curator's comment:
(added: 27 Nov 2019, 16:14:16, updated: 27 Nov 2019, 16:14:16)
Reproduced plot of Figure 1 in the original publication. Model simulated and plot produced using COPASI 4.24 (Build 197).