A University of Alberta pilot project is exploring whether combining a commercially available device with artificial intelligence can predict chronic respiratory symptoms in patients.
"The goal of this study is to see if the device is user-friendly enough to use at least three days per week for six months, which is the standard minimal follow-up time for respiratory diseases," project lead Dr. Giovanni Ferrara told Taproot.
The device is "able to track clinical signs and symptoms in an objective way, helping to inform treatment decisions tailored to patients' needs, thus providing a more precise control of their disease."
Researchers plan to enroll 40 patients with chronic lung diseases in the study. "Every patient will be enrolled for six months, so to complete this study we expect at least 12 to 18 months, depending on the speed of enrollment," said Dr. Ferrara.
Ferrara, who is also a professor with the University of Alberta Hospital's Division of Pulmonary Medicine, noted that Edmonton's innovation network makes this study possible.
"This environment is quintessential to enable real digital innovation in health," he said.
Ferrara told Taproot that there is a unique combination of expertise at the U of A, with a focus on the legal and administrative expertise at ST-Innovations, technical and engineering knowledge at the SMART network, and big data expertise at the Alberta Machine Intelligence Institute (Amii) and the faculty of engineering and computer science. He also highlighted the clinical expertise at the Northern Alberta Clinical Trial and Reserch Centre (NACTRC).
He said having all of these elements combined is key, because "we need to ensure the safety of the patients and the efficacy of the tools."
According to Ferrera, the U of A's Precision Health Innovation, Research and Technology Ecosystem (PRECISE) signature area is also crucial in supporting the project through facilitating the regulatory requirements and registration processes.
The Edmonton-based study will explore the possibility to predict when it's the right time to see a doctor based on the data collected by ADAMM RSM and artificial intelligence algorithms.
"We need to ensure the safety of the patients and the efficacy of the tools. The devices have to be tested in a rigorous way, as we do with drugs and diagnostic tests," said Ferrara.