COVID19 Rapid Diagnostic Testing [COVID-19]
Research type
Research Study
Full title
COVID19 Rapid Diagnostic Testing
IRAS ID
283201
Contact name
R La Ragione
Contact email
Sponsor organisation
University of Surrey
Duration of Study in the UK
0 years, 7 months, 31 days
Research summary
Research Summary
Urgent critical research is being undertaken to develop and optimise tests for Sars-CoV-2, the causative agent of COVID-19. A low cost portable diagnostic platform for the rapid detection of poultry infectious pathogens has been developed previously. This technology will now be diverted to help in the growing need for rapid COVID-9 diagnosis. In addition, an assay will be used to quantify the amount of virus present in clinical samples. In order to validate the tests and undertake the quantification RNA will be extracted from clinical samples from patients for the test. A collaboration has been set up with local NHS trusts to facilitate accessing the samples. The proposed test aims to provide results in <30 minutes.
Summary of Results
Accurate and rapid diagnostics paired with effective tracking and tracing systems are key to halting the spread of infectious diseases, limiting the emergence of new variants and to help monitor vaccine efficacy. The current Gold standard test (RT-qPCR) for COVID-19 is highly accurate and sensitive, but it is time consuming, and requires expensive specialised, lab-based equipment.
In this study, we developed and validated a SARS-CoV-2 (COVID-19) rapid and inexpensive diagnostic platform that relies on a reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay and a portable smart diagnostic device. Automated image acquisition and an Artificial Intelligence (AI) deep learning model embedded in the Virus Hunter 6 (VH6) device (https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fu2790089.ct.sendgrid.net%2Fls%2Fclick%3Fupn%3DXv3JSvJ-2B3M71ppf7N9agbY-2FYRQeAgzs8-2FwpW5Z2hgPcMtVroVDIZLDFzBjtpzj1SWT5w4XyMLaTz1o-2B73KNlRQ-3D-3D6pD8_E1aO2-2BZlVOSJJV-2FajQqskegTd6IRomHYTi-2Fbt8SH3YKlPxo9-2Bb05IhkGL7KK8lKGtnZyZOJyWFVy4ueeZbRZnERGlGt-2FIi9Lw33wnnVHfQRvj01la5hMJZsIsnqiWNheNt3bTDPvV8Sc-2BYHTWzdW50-2Bhy0iyLC3FPEpaqgs8C6XISwTnM43VhGK-2F9Rp344v-2FZFtdSH1YGAjveD8J4e4yPw-3D-3D&data=05%7C01%7CAshley.Totenhofer%40hra.nhs.uk%7Cfeb66e1b9479469cb85908db7ef317d8%7C8e1f0acad87d4f20939e36243d574267%7C0%7C0%7C638243355822392012%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=TcV1PEBlbuZPOoOoKmgWUWkeL99gBVLmBviTYMxE8Ew%3D&reserved=0 facilitated the avoidance of any subjectivity in the interpretation of results.
The VH6 device was linked to a smartphone companion application that registered patients (swab collection etc.) and managed the entire process, thus ensuring tests were traceable and data securely stored. The AI-implemented diagnostics platform developed in this study recognises the nucleocapsid protein gene of SARS-CoV-2 with high analytical sensitivity and specificity. A total of 752 NHS patient samples, 367 confirmed positives for coronavirus disease (COVID-19) and 385 negatives, were used for the development and validation of the test and the AI-assisted platform. The smart diagnostic platform was then used to test 150 positive clinical nasopharyngeal samples covering a dynamic range of clinically meaningful viral loads and 250 negative samples. When compared to RT-qPCR, our AI-assisted diagnostics platform was shown to be reliable, highly specific (100%) and sensitive (98 to 100% depending on viral load) with a limit of detection of 1.4 copies of RNA per μL in 30 minutes. Using this data, our CE-IVD and MHRA registered test and associated diagnostic platform was approved for medical use in the UK under the UK Health Security Agency's Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Laboratory and in-silico data presented here also indicates that the VIDIIA diagnostic platform is able to detect the main variants of concern in the UK (December 2022). Therefore, this system could provide an efficient, time and cost-effective platform to diagnose SARS-CoV-2 and other infectious diseases in resource-limited settings.REC name
East of England - Cambridge South Research Ethics Committee
REC reference
20/EE/0125
Date of REC Opinion
5 Jun 2020
REC opinion
Further Information Favourable Opinion