RT Journal Article SR Electronic T1 Rapid community-driven development of a SARS-CoV-2 tissue simulator JF bioRxiv FD Cold Spring Harbor Laboratory SP 2020.04.02.019075 DO 10.1101/2020.04.02.019075 A1 Yafei Wang A1 Randy Heiland A1 Morgan Craig A1 Courtney Davis A1 Ashlee N. Ford Versypt A1 Adrianne Jenner A1 Jonathan Ozik A1 Nicholson Collier A1 Chase Cockrell A1 Andrew Becker A1 Gary An A1 James A. Glazier A1 Aarthi Narayanan A1 Amber M. Smith A1 Paul Macklin YR 2020 UL http://biorxiv.org/content/early/2020/04/05/2020.04.02.019075.abstract AB The 2019 novel coronavirus, SARS-CoV-2, is an emerging pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors like diabetes. A critical question for treatment and protection is why it appears that the severity of infection may correlate with the initial level of virus exposure. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable “choke points” for pharmacologic interactions, screen potential therapies, and identify potential biomarkers that differentiate response dynamics. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce a prototype of a multiscale model of SARS-CoV-2 dynamics in lung and intestinal tissue that will be iteratively refined. The first prototype model was built and shared internationally as open source code and interactive, cloud-hosted executables in under 12 hours. In a sustained community effort, this model will integrate data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health.Note This is a rapid prototyping project. For the very latest, see http://covid19.physicell.org