IMVARIA's Fibresolve AI Biomarker Breakthrough Earns FDA Approval for Lung Fibrosis AMA Adopts New CPT Codes

IMVARIA, a cutting-edge health tech firm specializing in AI-driven digital biomarker solutions, announced today that the U.S. Food and Drug Administration (FDA) has granted marketing approval for Fibresolve. This groundbreaking digital biomarker solution utilizes artificial intelligence (AI) for a secure, non-invasive diagnosis of lung fibrosis, with a specific focus on idiopathic pulmonary fibrosis (IPF). Notably, this marks the inaugural FDA authorization for any diagnostic tool related to lung fibrosis and represents the first FDA Breakthrough-Designated AI diagnostic tool with simultaneously adopted CPT billing codes by the American Medical Association (AMA) in any medical condition.

Fibresolve acts as a valuable supplement for clinicians assessing patients with suspected lung fibrosis, providing a diagnostic subtype classification and potentially enabling earlier intervention. This breakthrough offers a cost-effective and practical AI solution for pulmonologists treating patients with lung disease.

Lung fibrosis, a life-threatening group of diseases affecting hundreds of thousands annually, especially IPF, is associated with a substantial delay in diagnosis and the potential for severe lung impairment or death within one to two years of onset. Fibresolve addresses this gap by employing AI-driven digital biomarkers to enhance diagnostic outcomes, meeting rigorous regulatory requirements for FDA approval.

The FDA's approval establishes Fibresolve as a billable digital diagnostic tool for clinicians, streamlining access to non-invasive diagnostic solutions that leverage digital biomarkers for lung fibrosis. This accomplishment builds on the FDA's previous recognition of Fibresolve as a Breakthrough Device, underscoring its significant impact on advancing digital healthcare through AI.

As a non-invasive option preceding more invasive alternatives, IMVARIA's AI-trained algorithm processes data from patients with suspected interstitial lung disease, providing clinicians with valuable supplementary information and a diagnostic subtype classification. This advancement aims to simplify the diagnostic process and facilitate timely and appropriate treatment decisions.


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