Originally published in Mass Device
physIQ announced today that the National Institutes of Health (NIH) entered into Phase II of a contract for its AI-based COVID-19 biomarker.
A Purdue University-affiliated artificial intelligence company, physIQ’s AI-based COVID-19 digital biomarker is being developed to address the rapid decompensation of high-risk COVID-19 patients, according to a news release.
physIQ’s technology’s cloud platform continuously collects and processes data from any wearable biosensor. In this case, the platform seeks out biomarkers to determine if a person infected with COVID-19 is experiencing a worsening in their condition.
Instead of using measurements such as temperature and pulse oximetry, physIQ’s platform offers multi-parameter vital signs and physiological features which establish a targeted biomarker (COVID-19 Decompensation Index — CDI) for worsening coronavirus-caused condition.
The contract option, exercised by the National Cancer Institute (NCI) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) of the NIH brings the total contract to $6.6 million for West Lafayette, Ind.-based physIQ.
Over the span of just 10 weeks, physIQ enrolled and monitored 400 high-risk COVID-19 patients in Phase I of the DeCODe study in collaboration with the University of Illinois Hospital & Health Sciences System (UI Health). The study aims to develop an early warning system to allow providers to intervene when a COVID-19 patient who is clinically surveilled from home has their condition worsen.
Phase II of the contract begins this month as 1,200 patients are slated to be enrolled to validate the digital biomarker, while physIQ will continue to enroll ambulatory patients who are confirmed COVID-19-positive.
“Using Phase I data, we developed and tested a preliminary digital biomarker using state of the art machine learning algorithms that take advantage of our extensive library of wearable biosensor analytics as inputs,” physIQ chief science officer Stephan Wegerich said in the release. “Furthermore, we were able to demonstrate performance levels that far exceeded our target performance criterion. We are looking forward to further validation in Phase II.”