Evidence map›Paper›PMID 39349243›Full record

ArticleSLAS technology2024

Development and validation of automated methods for COVID-19 PCR Master Mix preparation.

Giorgio Fedele, Graham Hill, Amelia Sweetford, Suki Lee, Bobby Yau, Domenico R Caputo, Denise Grovewood, Rowda Dahir, Paula Esquivias Ruiz-Dana, Anika Wisniewska and 5 more

Abstract read
In one paragraph

Article in SLAS technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Giorgio FedeleDepartment of Biology, Ecology and Earth Science, University of Calabria, Arcavacata, Italy.
Graham HillAnimal and Plant Health Agency, Weybridge, United Kingdom.
Amelia SweetfordIndependent Scholar.
Suki LeeDepartment of Biomolecular Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Bobby YauUniversity of Huddersfield, Huddersfield, United Kingdom.
Domenico R CaputoIndependent Scholar.
Denise GrovewoodSPT Labtech, Melbourn Science Park, United Kingdom.
Rowda DahirUniversity of Cambridge, Cambridge, United Kingdom.
Paula Esquivias Ruiz-DanaIndependent Scholar.
Anika WisniewskaIndependent Scholar.
Anna Di BiaseIndependent Scholar.
Miles GibsonHealth Protection Operations, UKHSA, United Kingdom.
Benita PercivalOmix Ltd, Birmingham, United Kingdom.
Stefan GrujicOmix Ltd, Birmingham, United Kingdom.
Donald P FraserOmix Ltd, Birmingham, United Kingdom. Electronic address: d.fraser@omix.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymerase chain reaction (PCR)-based assays were widely deployed during the SARS-CoV-2 pandemic for population-scale testing. High-throughput molecular diagnostic laboratories required a high degree of process automation to cope with huge testing demands, fast turnaround times, and quality requirements. However, process developers and optimizers often neglected the critical step of preparing a PCR Master Mix. The construction of PCR Master Mix depends on operator skill during the manual pipetting of reagents. Manual procedures introduce variation, inconsistency, wastage, and potentially risks data integrity. To address this, we developed a liquid-handler-based solution for automated, traceable, and compliant PCR Master Mix preparation. Here, we show that a fully automated PCR Master Mix protocol can replace manual pipetting, even in a diagnostic environment, without affecting accuracy or precision. Ultimately, this method eliminated operator-induced wastage and improved the consistency of the quality of results.

Indexed as

Automation, LaboratoryCOVID-19Polymerase Chain ReactionSARS-CoV-2COVID-19 Nucleic Acid TestingHumansAutomationCOVID-19High-throughputLiquid handlingMolecular diagnosticsPCR

Identifiers

PMID39349243
PMCPMC11639134

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.