Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/24502
Title: Enhancement of chemotherapy using oncolytic virotherapy: mathematical and optimal control analysis
Author: Malinzi, Joseph
Ouifki, Rachid
Eladdadi, Amina
Torres, Delfim F. M.
White, K. A. Jane
Keywords: Chemovirotherapy
Oncolytic virotherapy
Optimal drug and virus combination
Issue Date: 11-Jul-2018
Publisher: American Institute of Mathematical Sciences
Abstract: Oncolytic virotherapy (OV) has been emerging as a promising novel cancer treatment that may be further combined with the existing therapeutic modalities to enhance their effects. To investigate how OV could enhance chemotherapy, we propose an ODE based 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, OV 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 OV 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 Pontryagin's principle, to further refine predictions of the model with constant treatment rates by accounting for the treatment costs and sides effects.
Peer review: yes
URI: http://hdl.handle.net/10773/24502
DOI: 10.3934/mbe.2018066
ISSN: 1547-1063
Publisher Version: http://dx.doi.org/10.3934/mbe.2018066
Appears in Collections:SCG - Artigos

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