COVID-19 study to use continuous biosensor data, AI

May 07, 2021 // By Rich Pell
COVID-19 study to use continuous biosensor data, AI
Digital medicine company PhysIQ, Johns Hopkins University, Duke University, and The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) have announced a collaboration to deploy physIQ's biosensor data and analytics platform to support a clinical trial to evaluate investigational products for early treatment and post-exposure prophylaxis of COVID-19.

PhysIQ specializes in collecting and analyzing continuous physiological data acquired from wearable biosensors. In the 18-month Department of Defense-funded study, continuous monitoring with sophisticated personalized algorithms will be deployed to evaluate predictive power of physiologic signals to assess disease progression and provide early indication of infection. These signals, say the organizitions, will also support the evaluation of novel products for treatment and prevention of COVID-19.

PhysIQ says it will deploy its pinpointIQ platform at Johns Hopkins University and Duke University in support of the study. Confirmed COVID-19 positive individuals and patients at high risk of exposure will wear a clinical-grade biosensor that continuously streams data to pinpointIQ where advanced FDA-cleared analytics will process the raw biosensor data.

In addition to capturing continuous physiological data, patients will also use physIQ's mobile application to submit pulse oximeter measurements and report symptoms.

“Given the challenge of what appears to be an ever-evolving virus," says Dr. Danielle Clark, Co-founder and Director of the Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO) program, administered by HJF, and the protocol principal investigator, "the opportunity to deploy cutting-edge technology to study COVID-19 is paramount to ultimately understanding its progression and aid in the fight to defeat it. This is our second clinical study with physIQ and we are excited to expand our relationship by continuing to trial this innovative diagnostic technology."

Among the specific objectives of the study are to use continuous physiological data to characterize immune response to infection, evaluate novel machine-learning-enabled diagnostic and prognostic tools, and evaluate the efficacy of emergency investigational new drug therapies that may be administered to enrolled participants. For exploratory purposes, the study also seeks to identify baseline and longitudinal host and pathogen factors predictive of progression to guide clinical triage and treatment decision.

"We are excited to expand our long standing collaborative work with Dr. Clark and team up with our collaborators at Duke and Johns Hopkins," says Stephan Wegerich,


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