Jonguitud-Borrego, N;
Malcı, K;
Anand, M;
Baluku, E;
Webb, C;
Liang, L;
Barba-Ostria, C;
... Rios-Solis, L; + view all
(2022)
High—throughput and automated screening for COVID-19.
Frontiers in Medical Technology
, 4
, Article 969203. 10.3389/fmedt.2022.969203.
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Abstract
The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.
| Type: | Article |
|---|---|
| Title: | High—throughput and automated screening for COVID-19 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fmedt.2022.969203 |
| Publisher version: | https://doi.org/10.3389/fmedt.2022.969203 |
| Language: | English |
| Additional information: | Copyright © 2022 Jonguitud-Borrego, Malcı, Anand, Baluku, Webb, Liang, Barba-Ostria, Guaman, Hui and Rios-Solis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | diagnostic, COVID-19, high-throughput, automation, SARS-coV-2 |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10183100 |
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