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

传统上，体外和体内实验是研究病毒感染的唯一途径。这种获取知识的方法依赖于常识假设(例如，病毒数量越多意味着病毒越适合)。由于难以在不影响其他组件的情况下控制这些复杂系统的各个组件，这些假设经常未经检验。然而，数学和计算机模型(MCM)使我们有可能将一个实验系统解构为单独的组件，并确定这些组件是如何组合在一起产生我们观察到的感染的。病毒物理学是应用物理学的理论和方法来研究病毒的力学和动力学的生物物理学的一个重要分支。我的研究计划的长期目标是开发和改进MCMS，以准确地模拟在细胞培养物或宿主内传播的病毒感染。以MCMS的形式表达病毒感染的过程是至关重要的，因为它使我们能够预测并最终控制感染的过程和结果。这项建议的具体目标是开发新的MCM，用于：(1)有缺陷的干扰流感病毒颗粒的影响；(2)流感感染的空间分布和病毒在人类呼吸道内的传播；以及(3)丙型肝炎病毒感染在肝细胞培养中的传播。构建和验证MCM所需的实验数据是由我在流感(G.Boivin)和丙型肝炎(J.Feld)方面工作的合作者收集的。反过来，他们使用我的MCM的预测来评估，例如，出现抗药性病毒株的可能性，或者病毒复制周期的哪个方面是抗病毒药物的最佳靶点。随着病毒学实验方法的日益复杂，产生的大量定量数据排除了过去简单的统计分析：现在病毒学家与来自更传统的量化领域(如物理学)的研究人员合作是至关重要的。物理学家非常适合在这一领域做出重要贡献，我的团队是加拿大为数不多的进行这类研究的团队之一。

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.