MIT researchers have developed a new family multi-sample detection method for COVID-19.

One of the challenges of detecting COVID-19 is accurate and easy-to-use testing. Researchers from the California Institute of Technology have developed a new multi-way detection method that combines multiple data with sensors at a low cost to diagnose COVID-19 infections at home. The test is designed to quickly analyze small amounts of saliva or blood and can be done in less than 10 minutes without the need for a medical professional.

MIT researchers have developed a new family multi-sample detection method for COVID-19.

The team that invented the test came from Gao Wei’s lab, an assistant professor in the Department of Medical Engineering at the California Institute of Technology. Previously, Gao Wei and his team developed wireless sensors that monitor conditions, including glycation and stress levels, by detecting specific compounds with very low levels in blood, saliva or sweat. The sensors developed by the team use graphene, a form of carbon.

The sensor uses a laser-etched plastic sheet that produces a 3D graphene structure with tiny pores that form a large surface area on the sensor. The large surface area makes the sensor sensitive enough to detect compounds present in very small amounts of blood or saliva with high precision. The graphene structure on the sensor binds to antibodies that are sensitive to specific proteins, such as those on the surface of the COVID-19 virus.

Gao Wei calls this sensor SARS-CoV-2 RapidPlex. It contains antibodies and proteins that detect the virus itself, antibodies produced by the body to fight the virus, and inflammatory chemical markers that indicate the severity of the infection. Gao Wei says the sensors his team has developed are the only telemedicanic platforms he knows that can provide infection information in three types of data with one sensor.

So far, researchers have used the device only in the lab, obtaining small samples of blood and saliva from individuals who tested positive or negative for the virus for medical research. Preliminary studies have shown that the sensor is highly accurate, but researchers warn that real-world patients need to be tested to determine the accuracy of the sensor.