Researchers in the UK have developed a novel molecular diagnostic platform with AI assistance capable of detecting various COVID-19 variants and other infectious diseases.
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This portable and cost-effective device, named VIDIIA Hunter (VH6), has the potential to play a crucial role in averting future pandemics, owing to its accuracy and adaptability.
A collaborative effort involving scientists from the University of Surrey, Brunel University London, and Lancaster University, in partnership with the NHS, GB Electronics (UK) Ltd, and Vidiia Ltd, led to the creation of VH6.
The platform utilizes reverse transcription loop-mediated isothermal amplification (RT-LAMP) technology coupled with a deep learning model based on artificial intelligence (AI). This AI model has undergone training to interpret test results for infectious diseases, including COVID-19, eliminating user interpretation errors and enhancing overall accuracy.
Lateral flow tests are an efficient way of testing if you have COVID-19, however, there has always been a question mark over their accuracy which has only been heightened with the emerging number of variants now in circulation. As COVID-19 continues to evolve, we need to evolve with it and have highly accurate tests that can be readily used without the need for laboratory facilities.
Roberto La Ragione, Professor, Veterinary Microbiology and Pathology, University of Surrey
To validate the precision of VH6, researchers conducted tests on 150 clinical nasal swabs from individuals confirmed positive for COVID-19, encompassing a spectrum of viral loads. Additionally, 250 negative samples, sourced from NHS Berkshire, Surrey Pathology, and Royal Lancaster Infirmary, Lancaster, were used for comparison.
The results indicated a remarkably high accuracy, with a detection rate of 98% and a specificity of 100%. Further examinations demonstrated that the device successfully identified all the variants of COVID-19 that have been in circulation in the UK since December 2020.
The VH6 diagnostics platform has been approved for COVID-19 testing in the UK, but also has to potential to diagnose current and emerging infectious disease and antimicrobial resistance. Its portability, rapidity, accuracy, and affordability allow for near patient testing, in all laboratory and healthcare settings, including low-resources ones. The VIDIIA Hunter therefore has the potential to help control future outbreaks.
Dr Aurore Poirier, Study First, Co-Corresponding Author and Research Fellow B, University of Surrey
For surveillance and monitoring of COVID-19 and various infectious diseases, the test is linked to a smartphone application, enabling operators to oversee and trace patients and samples.
The app swiftly displays results and graphs within a brief timeframe of 20-30 minutes and seamlessly connects to a cloud platform. This system supports near-patient testing and holds the capability to identify additional infectious diseases like tuberculosis, dengue fever, and antimicrobial resistance.
Notably, this test stands out as it can be employed in both human and animal healthcare, representing a vital measure in detecting potential future zoonotic diseases that may transmitted between the two populations.
Incorporation of LAMP technology with advanced modules of AI has empowered the earliest, reliable and economical detection of infections, including COVID-19, and holds potential for the detection of diseases in both humans and animals, making it a tool of significant medical importance.
Muhammad Munir, Professor, Virology and Viral Zoonosis, Lancaster University
The VH6 has received official approval for medical use in the United Kingdom in accordance with the UK Health Security Agency’s Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Additionally, it carries the CE-IVD marking and is registered with the MHRA.
Journal Reference
Poirier, A. C., et al. (2023) VIDIIA Hunter: a low-cost, smartphone connected, artificial intelligence-assisted COVID-19 rapid diagnostic platform approved for medical use in the UK. Molecular Diagnostics and Therapeutics. doi.org/10.3389/fmolb.2023.1144001
Source: https://surrey.ac.uk/