About: CONTAIN: An open-source shipping container laboratory optimised for automated COVID-19 diagnostics

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About: CONTAIN: An open-source shipping container laboratory optimised for automated COVID-19 diagnostics Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	CONTAIN: An open-source shipping container laboratory optimised for automated COVID-19 diagnostics
Creator	Danovi, Davide Donora, Matthew Fleiss, Gosman, Aubin Jurkowski, Tomasz Mackenzie, Neil Meany, Thomas Oberacker, Phil Perkins, Alex Phillips, Alexander Pilch, Kjara Ramgoolam, Krishma Rares, Marius Steiner, Helene Thomas, Anthony Walker, Kenneth Zuckerman, Mark
Source	BioRxiv
abstract	The COVID-19 pandemic has challenged diagnostic systems globally. Expanding testing capabilities to conduct population-wide screening for COVID-19 requires innovation in diagnostic services at both the molecular and industrial scale. No report to-date has considered the complexity of laboratory infrastructure in conjunction with the available molecular assays to offer a standardised solution to testing. Here we present CONTAIN. A modular biosafety level 2+ laboratory optimised for automated RT-qPCR COVID-19 testing based on a standard 40ft shipping container. Using open-source liquid-handling robots and RNA extraction reagents we demonstrate a reproducible workflow for RT-qPCR COVID-19 testing. With five OT2 liquid handlers, a single CONTAIN unit reaches a maximum daily testing capacity of 2400 tests/day. We validate this workflow for automated RT-qPCR testing, using both synthetic SARS-CoV-2 samples and patient samples from a local NHS hospital. Finally, we discuss the suitability of CONTAIN and its flexibility in a range of diagnostic testing scenarios including high-density urban environments and mobile response units. Visual abstract
has issue date	2020-05-20(xsd:dateTime)
bibo:doi	10.1101/2020.05.20.106625
has license	biorxiv
sha1sum (hex)	b72f20dbe4155d82a02a898720519a978df27a6a
schema:url	https://doi.org/10.1101/2020.05.20.106625
resource representing a document's title	CONTAIN: An open-source shipping container laboratory optimised for automated COVID-19 diagnostics
schema:publication	bioRxiv
resource representing a document's body	covid:b72f20dbe4155d82a02a898720519a978df27a6a#body_text
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