Virus Diagnosis Device Delivers Lab-Quality Results within Three Minutes

Researchers have developed a device capable of delivering lab-grade viral diagnostic results in just three minutes, offering a rapid and economical solution for detecting COVID-19 from nasal swabs. This technology, according to its developers, is versatile enough to be modified for identifying various pathogens, such as bacteria, and potentially even cancer.

The prototype LoCKAmp device developed by engineers at the University of Bath (Bath, UK) uses advanced 'lab on a chip' technology. The device operates by quickly releasing and amplifying genetic material from a nasal swab sample and facilitating a chemical reaction that produces a result that can be viewed through a smartphone application. The LoCKAmp device differs from the common lateral flow tests used throughout the pandemic by employing the same genetic detection methods previously reserved for laboratory-grade PCR (polymerase chain reaction) tests, delivering rapid lab-level testing to the public for the first time. A key feature of the LoCKAmp is its rapid result time, clocking in at three minutes, making it the fastest COVID-19 test reported so far.

Built using readily available parts and mass-produced circuit boards, the LoCKAmp prototype device can be manufactured quickly and cost-effectively on a large scale. This presents an efficient new tool for healthcare providers and public health authorities globally in the field of virus detection. The research team suggests that with a commercial partner experienced in design and manufacturing, the LoCKAmp could be redesigned into a compact, portable device, ideal for use in areas with limited access to healthcare. Beyond just evaluating nasal swab samples, the LoCKAmp technology also has the potential for anonymous, community-level virus monitoring by testing samples from sources such as wastewater.

“This is an amazing display of the possibilities of lab-on-a-chip technology, and given the low cost and adaptability of the technology to detect a range of conditions, a potentially highly valuable and unique tool for a range of healthcare settings,” said Dr. Despina Moschou from the University of Bath who led the research.

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University of Bath

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