Machine Learning Enabled Electrochemical Biosensor Rapid Diagnostic Platform

The value of diagnostic tests and tools is undisputable whether it be for healthcare, homeland security, law enforcement, or environmental impact monitoring. While traditional diagnostic testing methods have progressed immensely in recent decades, there are still non-ideal aspects of common testing methods that prevent them from being more widely accessible2. For example, they are commonly analog (i.e., not always a simple yes/no result), use specialized equipment and require trained personnel. These lab diagnostics are also expensive and typically done in centralized labs, which requires time for transport and/or multi-day analysis as well complex sample preparation steps. In other words, for as far as we’ve come in recent decades, we still do not have diagnostic capabilities for most applications of need that can support in-field testing that is rapid, rugged, fast, affordable, reliable, and requires minimal user training. Relative to traditional molecular biology, spectroscopic, and other diagnostic technologies, electrochemistry-based sensors are well positioned to fill this market need and capability gap. Specifically, electrochemistry-based sensors have been shown to provide reliable, rugged, low-cost solutions for other applications. For example, electrochemical sensors are commonly used for smoke and carbon monoxide detectors, industrial gas sensors and other applications. However, electrochemistry-based detection and diagnostics for biological and healthcare applications are not yet common. This is an area of research that has been receiving increased attention from multiple research labs, including the well-known Whitesides Group’s uMed project at Harvard that demonstrated the capabilities of a low-cost portable and connected potentiostat with a cell phone using off the shelf screen printed electrodes (SPE). What’s still needed though is a turnkey product that provides an electrochemical diagnostic solution for the rapid detection of trace heavy metals, chemical, and biological threats.