Malinzi2018 - Enhancement of chemotherapy using oncolytic virotherapy

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<notes xmlns=""> <body xmlns=""> <pre>The paper describes a model of immune-cancer interaction. One time unit=24 days. Created by COPASI 4.25 (Build 207) This model is described in the article: Mathematical analysis of a tumour-immune interaction model: A moving boundary problem Joseph Malinzi and Innocenter Amima Mathematical Biosciences 308 (2019) 8–19 Abstract: IA spatio-temporal mathematical model, in the form of a moving boundary problem, to explain cancer dormancy is developed. Analysis of the model is carried out for both temporal and spatio-temporal cases. Stability analysis and numerical simulations of the temporal model replicate experimental observations of immune-induced tu- mour dormancy. Travelling wave solutions of the spatio-temporal model are determined using the hyperbolic tangent method and minimum wave speeds of invasion are calculated. Travelling wave analysis depicts that cell invasion dynamics are mainly driven by their motion and growth rates. A stability analysis of the spatio-tem- poral model shows a possibility of dynamical stabilization of the tumour-free steady state. Simulation results reveal that the tumour swells to a dormant level. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. Model is encoded by Jinghao Man and submitted to BioModels by Krishna Tiwari</pre> </body> </notes>
Related Publication
  • Enhancement of chemotherapy using oncolytic virotherapy: Mathematical and optimal control analysis.
  • Malinzi J, Ouifki R, Eladdadi A, Torres DFM, White JKA
  • Mathematical biosciences and engineering : MBE , 12/ 2018 , Volume 15 , Issue 6 , pages: 1435-1463 , PubMed ID: 30418793
  • Department of Mathematics and Applied Mathematics, University of Pretoria, Private Bag X 20, Hatfield, Pretoria 0028, South Africa.
  • Oncolytic virotherapy has been emerging as a promising novel cancer treatment which may be further combined with the existing therapeutic modalities to enhance their effects. To investigate how virotherapy could enhance chemotherapy, we propose an ODE based mathematical model describing the interactions between tumour cells, the immune response, and a treatment combination with chemotherapy and oncolytic viruses. Stability analysis of the model with constant chemotherapy treatment rates shows that without any form of treatment, a tumour would grow to its maximum size. It also demonstrates that chemotherapy alone is capable of clearing tumour cells provided that the drug efficacy is greater than the intrinsic tumour growth rate. Furthermore, virotherapy alone may not be able to clear tumour cells from body tissue but would rather enhance chemotherapy if viruses with high viral potency are used. To assess the combined effect of virotherapy and chemotherapy we use the forward sensitivity index to perform a sensitivity analysis, with respect to chemotherapy key parameters, of the virus basic reproductive number and the tumour endemic equilibrium. The results from this sensitivity analysis indicate the existence of a critical dose of chemotherapy above which no further significant reduction in the tumour population can be observed. Numerical simulations show that a successful combinational therapy of the chemotherapeutic drugs and viruses depends mostly on the virus burst size, infection rate, and the amount of drugs supplied. Optimal control analysis was performed, by means of the Pontryagin's maximum principle, to further refine predictions of the model with constant treatment rates by accounting for the treatment costs and sides effects. Results from this analysis suggest that the optimal drug and virus combination correspond to half their maximum tolerated doses. This is in agreement with the results from stability and sensitivity analyses.
Submitter of the first revision: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari

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isDescribedBy (1 statement)
PubMed 30418793

hasTaxon (1 statement)
Taxonomy Homo sapiens

hasProperty (2 statements)
Gene Ontology immune response to tumor cell
Mathematical Modelling Ontology Ordinary differential equation model

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  • Model originally submitted by : Krishna Kumar Tiwari
  • Submitted: Mar 5, 2020 1:39:03 PM
  • Last Modified: Mar 5, 2020 1:39:03 PM
  • Version: 2 public model Download this version
    • Submitted on: Mar 5, 2020 1:39:03 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Edited model metadata online.