About: Rapid community-driven development of a SARS-CoV-2 tissue simulator

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Rapid community-driven development of a SARS-CoV-2 tissue simulator
Creator	Wang, Yafei Rangamani, Padmini Narayanan, Aarthi Liu, Bing Shoemaker, Jason Islam, Mohammad Smith, Amber An, Gary Becker, Andrew Cockrell, Chase Collier, Nicholson Craig, Morgan Davis, Courtney Ford Versypt, Ashlee Heiland, Randy Jenner, Adrianne Macklin, Paul Ozik, Jonathan Hillen, Thomas Faeder, James Getz, Michael Gianlupi, Juliano Gla-Zier, James Hamis, Sara Hou, Dennis Kurtoglu, Furkan Macfarlane, Fiona Maygrundter, Pablo Morel, Penelope Pienaar, Elsje
Source	BioRxiv; Medline; PMC
abstract	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. 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 interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving rapid refinements with a two-to-four week release cycle. In a sustained community effort, this consortium is integrating 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.
has issue date	2020-07-29(xsd:dateTime)
bibo:doi	10.1101/2020.04.02.019075
bibo:pmid	32511322
has license	cc-by
sha1sum (hex)	02c21bef8cc81d14e19c41cf4888c48282cf2ba0
schema:url	https://doi.org/10.1101/2020.04.02.019075
resource representing a document's title	Rapid community-driven development of a SARS-CoV-2 tissue simulator
has PubMed Central identifier	PMC7239052
has PubMed identifier	32511322
schema:publication	bioRxiv
resource representing a document's body	covid:02c21bef8cc81d14e19c41cf4888c48282cf2ba0#body_text
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