Prediction of COVID-19 infection and clinical severity from blood-based biomarker fingerprints

The ongoing COVID-19 pandemic has put health care and the economy under pressure in large parts of the world, and one of the major challenges in reopening society is access to a rapid and reliable test for SARS-CoV2 infection. Our project focuses on developing a method that can detect viral infection at very early stages and at the same time may be able to predict the severity of the patient's disease course. The method is based on the so-called 'APTASHAPE' technology, where billions of small biosensor molecules, based on RNA, provide a snapshot of proteins and metabolites in the patient's blood. Traditional antibody-based tests for over-the-counter COVID-19 can only be performed 7-10 days after infection, while our system is based on the body's immediate response to an infection in the form of changes in blood composition, which occur as early as 6-12 hours. As our test is based on a very detailed picture of changes in the patient's blood, it may also be able to detect underlying disease history, which will have an impact on the COVID-19 course in the individual patient. The ultimate goal of our technology is to create a rapid screening platform that can reveal if a person has been infected within a few days and at the same time warn of any complications due to their underlying disease status.