A Mathematical Model for Tumor Growth and Treatment Using Virotherapy
College
College of Arts and Sciences
Department
Mathematics
Faculty Mentor
Zachary Abernathy, Ph.D., and Kristen Abernathy, Ph.D.
Abstract
We present a system of four nonlinear ordinary differential equations to model the use of virotherapy as a treatment for cancer. This model specifically describes the interactions among infected tumor cells, uninfected tumor cells, effector T-cells, and virions. Using local and global stability analysis techniques, we establish conditions on model parameters to ensure a stable cure state of the full model as well as various submodels. We illustrate these dynamics through numerical simulations of the model using estimated parameter values from the literature, and we conclude with a discussion on the biological implications of our results.
Recognized with an Award?
2nd Place, Life Science Oral Presentations, SAEOPP McNair/SSS Scholars Research Conference, June 2017
Previously Presented/Performed?
SAEOPP McNair/SSS Scholars Research Conference, Atlanta, GA, June 2017; McNair Summer Research Symposium, Winthrop University, June 2017; Summer Undergraduate Research Experience (SURE) Symposia, Winthrop University, June and September 2017; Regional Mathematics and Statistics Conference, University of North Carolina, Greensboro, November 2017
Grant Support?
Supported by a Ronald E. McNair Post-Baccalaureate Achievement Program grant from the U.S. Department of Education
Start Date
20-4-2018 12:45 PM
A Mathematical Model for Tumor Growth and Treatment Using Virotherapy
West 221
We present a system of four nonlinear ordinary differential equations to model the use of virotherapy as a treatment for cancer. This model specifically describes the interactions among infected tumor cells, uninfected tumor cells, effector T-cells, and virions. Using local and global stability analysis techniques, we establish conditions on model parameters to ensure a stable cure state of the full model as well as various submodels. We illustrate these dynamics through numerical simulations of the model using estimated parameter values from the literature, and we conclude with a discussion on the biological implications of our results.
