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Results of Research on Identification of Covid-19 Viruses Utilizing Advantest’s nanoSCOUTER Fine Particle Measurement Instrument Published in Nature Communications

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nanoSCOUTER: Leading semiconductor test equipment supplier Advantest Corporation (TSE: 6857) has announced that the results of a clinical study on the identification of COVID-19 viruses using the company’s nanoSCOUTER™ fine particle measurement instrument were published in Nature Communications, a peer-reviewed scientific journal, on June 17th1. In the study, 100 saliva samples (50 negative for Covid-19 and 50 positive) were measured and analyzed within 5 minutes each. Sensitivity (the ability of the test to correctly identify positive samples) of 90% and specificity (the ability of the test to correctly identify negative samples) of 96% were achieved.

A research group of the Institute of Scientific and Industrial Research at Osaka University is studying virus testing methods using the AI-based particle identification system developed by Aipore Inc.2 and the nanoSCOUTER™. The method used in the just-published study identifies viral particles by passing them through a nanoscale hole, through which a microcurrent is passed, and applying AI machine-learning to the highly accurate current waveform thus obtained. The results of this research3 can be expected to facilitate immediate diagnoses in hospitals as well as viral screening for large gatherings. In addition, machine-learning can be applied to many types of viruses, enabling early detection of novel pathogens.

The nanoSCOUTER™ is a lightweight, desktop-sized fine particle measurement instrument that utilizes a precise nanopore (nanometer-scale pore) sensor module made with semiconductor manufacturing processes and Advantest’s proprietary microcurrent measurement technology. It measures the quantity and particle size of fine particles on the order of 100 nanometers, such as viruses, exosomes4, and liposomes5, with great speed and accuracy. In addition, when the nanoSCOUTER™ is used in conjunction with Aipore Inc.’s AI-based particle identification system, it is possible to quickly identify the type of particles detected. At the present time, the product is a scientific instrument, not an approved medical device.

Rapid and accurate testing methods, along with vaccines and therapeutic agents, are important measures for prevention of Covid-19 spread. Based on Advantest’s corporate mission of “enabling leading-edge technologies,” the company will strive to further develop this technology so that the nanoSCOUTER™ can contribute to solving these vital issues.


1 “Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection,” Masateru Taniguchi, Shohei Minami, Chikako Ono, Rina Hamajima, Ayumi Morimura, Shigeto Hamaguchi, Yukihiro Akeda, Yuta Kanai, Takeshi Kobayashi, Wataru Kamitani, Yutaka Terada, Koichiro Suzuki, Nobuaki Hatori, Yoshiaki Yamagishi, Nobuei Washizu, Hiroyasu Takei, Osamu Sakamoto, Norihiko Naono, Kenji Tatematsu, Takashi Washio, Yoshiharu Matsuura, and Kazunori Tomono
https://www.nature.com/articles/s41467-021-24001-2

2 Aipore Inc. was established in 2018 as a result of the Japanese Cabinet Office’s national project “Impulsing Paradigm Change through Disruptive Technologies Program (ImPACT)”. Using Advantest’s nanoSCOUTER™, Aipore has developed a solution for AI analysis of measurement data of bioparticles such as viruses and bacteria.
https://aipore.com/

3 The Japan Agency for Medical Research and Development (AMED) subsidized this research as a part of its Reiwa 2 virus infection prevention technology development project “Research on COVID-19 test methods using nanopore technology and machine learning.”

4 Exosomes: Nano-order particles secreted from cells that contain any of various biomolecules, such as proteins or nucleic acids. Exosomes hold promise as diagnostic tools in medicine.

5 Liposomes: Closed, spherical lipid bilayers, often used as vehicles for pharmaceuticals.

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