Handheld Viral Test and Epidemiological Surveillance Network
Problem
Rapidly identifying positive cases of viral infections (e.g. COVID-19) is critical to preventing and/or containing viral outbreaks and pandemics. Existing testing methodology relies on sparsely distributed centralized testing facilities, resulting in delays due to transportation, testing throughput, and distribution of test results, which impedes reports and tallying of information about propagation of the virus. Likewise, laboratory instruments are expensive limiting wide scale distribution.
Solution
A cost effective, handheld mobile diagnostic system, which can instantly create (or augment) an epidemiological surveillance network (ESN) is of immediate need. The iFirst Analyzer can detect specific viruses using an hemagglutination/agglutination assay. Hemagglutination/Agglutination assays are proven methods of detecting the presence of both antibodies and viruses and have historically been used in laboratory settings. iFirst Medical Technologies, Inc. specializes in taking sophisticated laboratory tests and integrating them into low-cost, single-use, microfluidic/BioMEMS cartridges. Using advanced computer learning and machine-vision algorithms, specimen-laden cartridges are optically interrogated to rapidly obtain results. Optically based algorithms replace the eyes of the technician and provide scalable means to integrate results into GIS-based heatmaps (Figure 1). The iFirst analyzer uses the camera and powerful microprocessors within the iPhone; together the phone, single-use cartridges, and software from iFirst combine forces to provide rapid diagnostic results.
Figure 1. Example of GIS-based Heatmap of viral outbreak
​
Proposed Plan
iFirst has begun the development of a COVID-19 assay, based on iFirst’s multi-well hemagglutination/agglutination cartridge. This cartridge will rapidly test a nasal swab specimen to detect viruses in endothelial cells. The iFirst analyzer features 4G LTE connectivity, GPS and powerful microprocessors, which will upload results in real-time into an epidemiological surveillance network (ESN). iFirst’s existing diagnostics cloud services will be used to create the EPN, which can be further integrated with existing surveillance networks operated by organizations such as the CDC and WHO.
iFirst has, and continues to develop algorithms that use computer vision, machine learning, and artificial intelligence to identify positive agglutination/hemagglutination reactions. An example of one of these techniques is shown in Figure 2. The top image shows edge detection being used to identify a positive reaction. iFirst originally developed hemagglutination/agglutination assays for other applications and can leverage this previous work to apply to the detection of COVID-19 virus and/or antibodies. By using a computer vision, machine learning and artificial intelligence we can greatly increase sensitivity and detect weak positive reactions.
Figure 2. Edge detection, one of many computer vision and machine learning techniques used in Positive identification
​
The iFirst analyzer is ready for mass production and has engaged testing with Underwriters Laboratories (UL) and expects to complete UL testing and CE mark certification of the iFirst Analyzer during the second quarter of 2020. The CE mark indicates that a product may be sold freely in any part of the European Economic Area, irrespective of its country of origin. iFirst will be seeking expedited FDA approval to meet the needs of the current outbreak.