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Award Details

Mathematical and computer models of viral infection dynamics within a host or a cell culture

Research Details
Competition Year: 2013 Fiscal Year: 2013-2014
Project Lead Name: Beauchemin, Catherine Institution: Ryerson University
Department: Physics Province: Ontario
Award Amount: $18,000 Installment: 1 - 5
Program: Discovery Grants Program - Individual Selection Committee: Physics
Research Subject: Physics Area of Application: Advancement of knowledge
Co-Researchers: No Co-Researcher Partners: No Partners
Award Summary

Experimentation in vitro and in vivo has traditionally been the only way to study viral infections. This approach for deriving knowledge relies on common-sense assumptions (e.g., a higher viral count means a fitter virus). These assumptions often go untested due to difficulties controlling individual components of these complex systems without affecting others. Mathematical and computer models (MCMs), however, make it possible to deconstruct an experimental system into individual components and determine how the pieces combine to create the infection we observe. Virophysics is an important branch of biophysics in which the theories and methods of physics are applied to study the mechanics and dynamics of viruses. The long-term objective of my research programme is to develop and improve MCMs to accurately model viral infection spread within a cell culture or a host. Expressing the process of viral infection in the form of MCMs is essential because it enables us to predict and, ultimately, control the course and outcome of an infection. The specific aims of this proposal are to develop new MCMs for: (1) the effect of defective interfering flu virus particles; (2) the spatial distribution of a flu infection and transport of the virus within the human respiratory tract; and (3) the spread of hepatitis C virus infections in liver cell cultures. Experimental data required to construct and validate the MCMs are collected by my collaborators working with influenza (G. Boivin) and hepatitis C (J. Feld). They, in turn, use my MCMs' predictions to evaluate, for example, the likelihood of emergence of a drug-resistant virus strain or what aspect of a virus' replication cycle is the optimal target for antiviral drugs. With the increasing sophistication of experimental methods in virology, the vast amount of quantitative data generated precludes the simple statistical analyses of the past: it is now critical for virologists to collaborate with researchers from more traditionally quantitative fields such as Physics. Physicists are ideally suited to make important contributions in this area, and my group is one of the few conducting this type of research in Canada.