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Mathematical Modelling of T Cell Infection during Oncolytic Viral Therapy

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Title: Mathematical Modelling of T Cell Infection during Oncolytic Viral Therapy
Author: Carson, Emilee L.
Department: Department of Mathematics and Statistics
Program: Mathematics and Statistics
Advisor: Willms, Allan R.
Abstract: Oncolytic viral therapy is an increasingly promising cancer treatment using a virus to infect and kill cancer cells, but not normal cells. Initially it was thought that doses with more virus would lead to more cancer cell death, and that injecting the virus more frequently would help to maximize the infection. However, it has been shown that injecting the host with more virus can lead to the infection and hence death of CD4+ and CD8+ T cells, a detrimental effect. A mathematical model of this phenomena is developed and fit to experimental data. Using this model, we show that the time needed between doses to ensure that the T cells are not at a greater risk of infection is longer than what is used in most dosing protocols. We also show that more than 60% of CD4+ or 80% of CD8+ T cells may become infected via an oncolytic virus.
URI: http://hdl.handle.net/10214/17979
Date: 2020-05
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