PROJECT SUMMARY The parent award for this project is the Center for Modeling Complex Interactions (CMCI), which focuses on an approach that can be used to address many biomedical problems. This approach is team-based interdisciplinary research with the goal of integrating modeling into biomedical research projects. CMCI supports modelers by giving them opportunities to integrate into interdisciplinary teams and empiricists by providing them access to relevant modeling expertise. This creates a community and a culture to facilitate interdisciplinary research and enhances the rigor of biomedical research. Following the structure of CMCI, we will build an interdisciplinary team with a shared scientific interest to understand the time and space-dependent roles of type I interferon (IFN-I) responses in controlling respiratory viral infection and limiting inflammation. The proposed research activities include mathematical and computational approaches that will be informed and validated by data generated from cell culture infection studies and mouse lung tissue samples from previous infection studies. An innovative 2D spatiotemporal model of the lung will be built and visualized in virtual reality. By using a tandem mathematical-experimental approach, we will predict temporal dynamics of IFN-I (Aim 1) and uncover unforeseen spatial connections in an augmented reality environment of IFN-I during influenza virus infection (Aim 2). To develop and evaluate the predictive power of these innovative models, we propose forming an interdisciplinary collaboration between scientists of the Departments of Biology, Mathematics, and Virtual Technology and Design at the University of Idaho. The combined expertise in virology, immunology, mathematics, and virtual technology is critical for addressing the complexity of IFN-I roles during influenza virus infection. The knowledge gained through this project will lead to the development of immune-based therapeutics for influenza and other respiratory viral infections. Further, this project will create a community and a culture to facilitate interdisciplinary research at the University of Idaho.

NARRATIVE A quantitative understanding of viral dynamics and immunity in the lungs holds enormous promise for reducing the severity of respiratory viral infections. Computational models will be developed for predicting the multidimensional time and spatial characteristics of innate immune responses to influenza virus infection in the lung. Without such a mathematical framework, the design of therapies will be slowed, or worse, dangerous, and faulty.