Event Title

A Mathematical Model for Tumor Growth and Treatment Using Virotherapy

Faculty Mentor

Zachary Abernathy, Ph.D., and Kristen Abernathy, Ph.D.

College

College of Arts and Sciences

Department

Department of Mathematics

Location

West 221

Start Date

20-4-2018 12:45 PM

Description

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.

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

Awards Won

2nd Place, Life Science Oral Presentations, SAEOPP McNair/SSS Scholars Research Conference, June 2017

Comments

Jessica is a McNair Scholar.

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Apr 20th, 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.