IMVARIA Inc., a health tech company focusing on AI-driven digital biomarker solutions, announced that the U.S. Food and Drug Administration (FDA) has granted marketing authorization for the use of Fibresolve, an digital biomarker solution that uses artificial intelligence to guide safe, non-invasive diagnosis of lung fibrosis with a focus on idiopathic pulmonary fibrosis (IPF). This signifies the first ever FDA authorization of a diagnostic tool of any type in lung fibrosis, and the first FDA Breakthrough-Designated AI diagnostic tool with simultaneously adopted CPT billing codes by the American Medical Association (AMA) in any disease, according to the company.
“Fibresolve serves as an adjunct to clinicians in assessing patients with suspected lung fibrosis to provide a diagnostic subtype classification, potentially facilitating proper treatments at an earlier stage of the disease process,” says Joshua Reicher, MD, co-founder and CEO of IMVARIA. “The FDA’s authorization of Fibresolve marks a significant milestone, not only for lung fibrosis patients, but also for the advancement of AI-based healthcare technologies. The medical community, along with health insurance companies, now has a viable, cost-effective option making AI highly practical, useful, and easy to incorporate into medical practice for the thousands of pulmonologists who treat patients with lung disease.”
Lung fibrosis is a life-threatening group of diseases that affect hundreds of thousands of people every year, with IPF the most devastating. Traditionally, existing therapies for this disease are expensive and, if given to the wrong patients, potentially toxic. On average, this condition carries a nearly two-and-a-half-year delay in the diagnosis from the initial manifestation of symptoms. Meanwhile, severe lung impairment and even death can happen within one to two years from the onset of lung fibrosis. To deliver on the promise of AI-driven digital biomarkers to improve the outcomes for patients, IMVARIA developed Fibresolve as a groundbreaking innovation and met stringent regulatory requirements to earn FDA authorization.
“It’s important to have new and validated options, such as Fibresolve, for those patients at risk of IPF,” says Joshua Mooney, MD, MS, clinical assistant professor, Medicine – Pulmonary, Allergy & Critical Care at Stanford Medicine, and a board certified pulmonologist and critical care physician who specializes in the care of interstitial lung disease and lung transplant patients. “I look forward to seeing the positive impact of Fibresolve on lung fibrosis patients across the nation.”
The FDA authorization of IMVARIA’s lead product Fibresolve, as a billable digital diagnostic tool for clinicians to use for patients, will expedite the medical community’s access to a non-invasive diagnostic solution using digital biomarkers in a novel way for lung fibrosis. This new authorization builds on the past medical and scientific assessments that the FDA had previously completed in assigning Fibresolve Breakthrough Device Designation.
“For people living with the rapidly deteriorating symptoms of this rare, yet deadly disease, the FDA authorization of Fibresolve offers real hope, while giving doctors who treat these patients a new, powerful tool that is designed to save lives and reduce suffering at an exponential rate that only AI can deliver,” says Michael Muelly, MD, co-founder and CTO of IMVARIA. “This truly is a major step forward in advancing digital healthcare through the use of AI in the hands of medical doctors.”
As an option before other more invasive options are considered, data from patients with suspected interstitial lung disease is run through IMVARIA’s AI-trained algorithm to provide non-invasive adjunct information, a diagnostic subtype classification, helping drive diagnosis and setting the patient on a pathway to be given an appropriate treatment on a more timely basis. In addition to the health benefits, this is expected to save thousands of dollars per person for each test, with the cost savings going back into the health system.
