Evidence map›Paper›PMID 32900994›Full record

ArticleNature communications2020

A role for Biofoundries in rapid development and validation of automated SARS-CoV-2 clinical diagnostics.

Michael A Crone, Miles Priestman, Marta Ciechonska, Kirsten Jensen, David J Sharp, Arthi Anand, Paul Randell, Marko Storch, Paul S Freemont

Erratum issuedAbstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. Nipah virus: pathogenesis, genome, diagnosis, and treatment.Applied microbiology and biotechnology · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Michael A CroneLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK.ORCID http://orcid.org/0000-0002-5675-0172
Miles PriestmanLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK.ORCID http://orcid.org/0000-0002-0811-354X
Marta CiechonskaLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK.ORCID http://orcid.org/0000-0003-1165-6921
Kirsten JensenLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK.
David J SharpUK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK.
Arthi AnandHistocompatibility and Immunogenetics Laboratories, Department of Infection and Immunity, North West London Pathology, London, UK.
Paul RandellDepartment of Infection and Immunity, North West London Pathology, London, UK.
Marko StorchLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK.ORCID http://orcid.org/0000-0003-1503-8282
Paul S FreemontLondon Biofoundry, Imperial College Translation and Innovation Hub, White City Campus, 80 Wood Lane, London, W12 0BZ, UK. p.freemont@imperial.ac.uk.ORCID http://orcid.org/0000-0002-5658-8486

Funding

Department of Health NIHR-RP-011-048
6 · The paper itself

Abstract

The SARS-CoV-2 pandemic has shown how a rapid rise in demand for patient and community sample testing can quickly overwhelm testing capability globally. With most diagnostic infrastructure dependent on specialized instruments, their exclusive reagent supplies quickly become bottlenecks, creating an urgent need for approaches to boost testing capacity. We address this challenge by refocusing the London Biofoundry onto the development of alternative testing pipelines. Here, we present a reagent-agnostic automated SARS-CoV-2 testing platform that can be quickly deployed and scaled. Using an in-house-generated, open-source, MS2-virus-like particle (VLP) SARS-CoV-2 standard, we validate RNA extraction and RT-qPCR workflows as well as two detection assays based on CRISPR-Cas13a and RT-loop-mediated isothermal amplification (RT-LAMP). In collaboration with an NHS diagnostic testing lab, we report the performance of the overall workflow and detection of SARS-CoV-2 in patient samples using RT-qPCR, CRISPR-Cas13a, and RT-LAMP. The validated RNA extraction and RT-qPCR platform has been installed in NHS diagnostic labs, increasing testing capacity by 1000 samples per day.

Indexed as

BetacoronavirusBiological AssayClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingCRISPR-Cas SystemsHumansMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesPandemicsPneumonia, ViralReal-Time Polymerase Chain ReactionRNA, ViralSARS-CoV-2Sensitivity and SpecificityRNA, Viral

Identifiers

PMID32900994
PMCPMC7479142

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.