Validated models of immune response to virus infection. Issue 12 (December 2018) - Smith, Amber M.
Abstract: Viruses are a main cause of disease worldwide and many are without effective therapeutics or vaccines. A lack of understanding about how host responses work to control viral spread is one factor limiting effective management. How different immune components regulate infection dynamics is beginning to be better understood with the help of mathematical models. These models have been key in discriminating between hypotheses and in identifying rates of virus growth and clearance, dynamical control by different host factors and antivirals, and synergistic interactions during multi-pathogen infections. A recent focus in evaluating model predictions in the laboratory and clinic has illuminate the accuracy of models for a variety of viruses and highlighted the critical nature of theoretical approaches in virology. Here, I discuss recent model-driven exploration of host-pathogen interactions that have illustrated the importance of model validation in establishing the model's predictive capability and in defining new biology. Highlights: Kinetic models of host-pathogen interactions identify important regulatory mechanisms. In silico experiments are rapid, insightful, and aid hypothesis discrimination. Model-driven experimental studies significantly improve biological insight. Experimentally validating kinetic models maximizes their predictive capabilities.