07Feb

Nanopore Sensor Exploits Artificial Intelligence for Specific Virus Detection

Researchers at Osaka University in Japan have developed a nanopore sensor to detect single influenza viral particles in a biological sample. The researchers used artificial intelligence to work out the “hallmarks” of the virus, which allowed them to identify it using the sensor. The technique has potential as a point-of-care diagnostic tool for influenza patients, which could be very helpful in case of a dangerous outbreak.

Influenza infects millions of people every year. In vulnerable patients, such as the elderly, the infection can prove fatal, and there is an ever-present risk of a global flu pandemic, which could have catastrophic consequences. Given that the virus is highly contagious, in the case of a dangerous flu outbreak, rapid, sensitive and accurate diagnosis is extremely important, ideally at the point of care.

Current methods to identify the virus include genetic techniques, but conventionally these are not particularly rapid, and can require highly trained staff and specialized laboratory equipment, making them difficult to apply at the point of care.

To overcome this issue, this research group devised a new diagnostic approach that combines artificial intelligence with a nanopore sensor. The sensor involves creating a flow of liquid through a nanopore using an electric current that spans the pore.

The system allows only viral particles to pass through the nanopore, meaning that the sensor is highly specific, even when analyzing complex biological fluids containing numerous components. The device is also extremely sensitive, theoretically allowing the detection of single viral particles. The researchers used an artificial intelligence technique to identify the viral signature.

“We used machine-learning analysis of the electrical signatures of the virions,” said Makusu Tsutsui, a researcher involved in the study. “Using this artificial intelligence approach to signal analysis, our method can recognize a slight current waveform difference, which cannot be discerned by human eyes. This enables high-precision identification of viruses.”

The system may also be useful in detecting other types of virus, suggesting that it could be deployed in a variety of contexts for rapid point-of-care diagnosis.

“Our testing revealed that this new sensor may be suitable for use in a viral test kit that is both quick and simple,” said Akihide Arima, another researcher involved in the study. “Importantly, use of this sensor does not require specialized human expertise, so it can readily be applied as a point-of-care screening approach by a wide variety of healthcare personnel.”

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