COVID-19 not only has a range of symptoms, but also varying impact on patients. In its early stages, doctors are unable to predict the progression of the disease because it depends on the interaction between the viral infection, the patient’s response, and the development of cardiovascular inflammation. To address that problem, a cross-disciplinary program spearheaded by EPFL seeks to empower both patients and doctors with an assistive, predictive, and personalized healthcare tool called Digipredict.
Digipredict is a pan-European research program involving universities, hospitals, and startups. It aims to develop a digital twin that can detect serious complications in COVID-19 patients by using breakthrough technology in the fields of artificial intelligence, smart patches, and organs-on-chips. Playing a key role in the project are EcoCloud faculty members David Atienza and Martin Jaggi, who also head the Embedded Systems Laboratory and the Machine Learning and Optimization Laboratory respectively. The two other EPFL laboratories involved in the project are the Nanoelectronic Devices Laboratory and the Laboratory of Movement Analysis and Measurement.
Digipredict detects the first signs of a ‘cytokine storm’ in high-risk COVID-19 patients, thus allowing doctors to act before it causes serious damage to the cardiovascular systems. Cytokines are proteins that play an important role in normal immune responses, but having a large amount of them released in the body all at once can be harmful.
Digipredict predicts disease progression by using a smart patch with integrated technology for collecting crucial medical data such as blood oxygen levels, breathing rate and body temperature. Nanosensors linked to an AI program track specific biomarkers that indicate any possibility of a cytokine storm. The data collected and analyzed by Digipredict allows doctors to make informative and timely decisions about the course of treatment.
Apart from EPFL, other institutions involved in the project are the University of Twente, ETH Zurich, IMEC in Belgium, Stichting Imec in the Netherlands, the Charité university hospital in Berlin, the University of Bern (through Inselspital), and three startups (Ascilion, EPOS-IASIS, and SCIPROM). The Center for Intelligent Systems (CIS) will be responsible for promoting Digipredict and disseminating its findings.