Medibyt gets FDA clearance after CPETWise cuts interpretation time by over 50%

Medibyt Ltd. has secured U.S. Food and Drug Administration (FDA) 510(k) clearance for CPETWise, moving its cardiopulmonary exercise-testing software from development and demonstration into a regulated U.S. commercialization phase. FDA records show the traditional 510(k) application was received on January 26 and cleared on August 20 as substantially equivalent under the Class II pulmonary-function predicted-values category, with Medibyt announcing the regulatory decision on September 1. The platform is designed to standardize CPET analysis, interpretation and reporting while retaining clinician access to underlying physiological data rather than replacing medical judgment with a closed automated output. Medibyt enters commercialization with an unusually practical value proposition for clinical software: a 100-case University of Washington proof-of-concept evaluation reported more than a 50% reduction in interpretation time and average user satisfaction of 4.5 out of five.

The company is privately held and has not disclosed revenue, valuation, product pricing or the amount of capital available for commercialization, which limits financial analysis. Medibyt has nevertheless begun a commercial pilot with a U.S. CPET company and says demonstration environments are already operating at institutions including Columbia University, the University of Washington, University of California Los Angeles, Sheba Medical Center and Ichilov Medical Center. Those deployments give the company clinical reference sites before a broader sales push, while its next commercial challenge is proving that faster interpretation translates into enough laboratory productivity to justify software purchasing and integration costs.

Why is cardiopulmonary exercise testing difficult enough to justify dedicated software?

Cardiopulmonary exercise testing measures how the cardiovascular, pulmonary and metabolic systems respond together as a patient exercises under controlled conditions. Clinicians can use the resulting information when evaluating unexplained exercise intolerance, heart failure, pulmonary disease, transplant candidates and other complex conditions in which resting measurements do not reveal how the body behaves under stress. The strength of CPET is the number of physiological signals generated simultaneously, but that same richness makes interpretation time-consuming and dependent on specialist expertise.

Traditional analysis can involve reviewing oxygen consumption, carbon dioxide production, ventilatory efficiency, heart-rate response, blood pressure, oxygen saturation and numerous derived relationships before determining what physiological system most likely limits exercise. Medibyt is trying to automate the repetitive analytical and reporting layers while keeping raw measurements and standardized graphical panels visible to the clinician. That positioning is important because the company is selling workflow support rather than claiming the software autonomously diagnoses cardiopulmonary disease.

FDA classification reinforces that distinction. CPETWise was cleared under regulation 21 CFR 868.1890 as a Class II device categorized as a calculator of predicted pulmonary-function values. The decision was based on substantial equivalence through the traditional 510(k) pathway rather than a De Novo classification or Premarket Approval, and the submission underwent third-party review. Calling CPETWise “FDA approved AI” would therefore overstate its actual regulatory status.

What does the 100-case University of Washington study say about workflow economics?

Medibyt reported that a proof-of-concept study involving 100 CPET cases at the University of Washington reduced interpretation time by more than 50% while generating an average user-satisfaction score of 4.5 out of five. The software automatically identifies a primary physiological limiting factor, generates structured reports and presents standardized graphical panels, allowing clinicians to concentrate on interpretation rather than manually assembling each element of the test. The company has not disclosed the complete dataset required to calculate economic savings per physician or per laboratory, so the time-reduction finding should be viewed as evidence of workflow potential rather than a demonstrated return on investment across all care settings.

A greater-than-50% reduction could nevertheless matter disproportionately in high-volume centers because specialist time is one of the scarce resources constraining sophisticated diagnostic services. If a physician who currently interprets ten studies during a fixed session can reliably handle substantially more without sacrificing accuracy or oversight, the laboratory can potentially improve capacity without adding equivalent specialist headcount. The economics become stronger where patient demand exceeds available expertise and weaker in low-volume centers where interpretation time is not the principal operating bottleneck.

Standardization could be equally important. Different clinicians may organize and report the same physiological information differently, complicating comparisons across sites and longitudinal studies. A software platform that imposes consistent calculations and graphical presentation can make multi-center research, referral networks and longitudinal patient monitoring easier even when it does not directly reduce staffing.

Why could hardware partnerships determine whether CPETWise scales in the United States?

CPETWise is software sitting on top of data generated by existing exercise-testing equipment, so its commercial adoption depends heavily on integration. Hospitals are less likely to buy a workflow tool that requires extensive manual transfer or creates a second disconnected system beside equipment they already use. Medibyt said it has started a commercial pilot with a leading U.S. CPET company to integrate CPETWise with existing hardware and streamline diagnostic data transfer, while international manufacturers have also expressed interest in partnerships.

That creates several possible business models. Medibyt could sell directly to hospitals and clinics, license software through CPET equipment manufacturers or embed the platform into broader cardiopulmonary diagnostic systems. Manufacturer partnerships may compress the company’s share of economics per customer, but they can also provide distribution scale and reduce the integration burden that often slows independent medical software companies.

The company is simultaneously building future machine-learning models using access to approximately 4,000 retrospectively interpreted CPET records. Those data could support more advanced assistance if development and validation are successful, although new functionality that materially changes the device’s intended use may require additional regulatory review. Medibyt has also identified spirometry, BodyBox pulmonary-function testing, sports medicine and performance testing as possible extensions beyond CPET.

Can a private software company convert FDA clearance into sustainable clinical adoption?

Regulatory clearance solves only one part of a healthcare software business model. Medibyt still needs hospital procurement, information-security review, integration with existing devices and electronic records, physician training and evidence that the platform maintains performance across different patient populations and laboratories. Buyers will also want to know whether efficiency savings exceed subscription or licensing costs, information the company has not publicly disclosed.

The initial reference sites give Medibyt credibility because large academic institutions can help establish workflow evidence and physician familiarity. They do not automatically prove a scalable commercial model, particularly when smaller hospitals may lack dedicated CPET programs or sufficient case volumes to justify another software product. The U.S. pilot with an equipment company therefore may be more commercially revealing than another demonstration deployment.

CPETWise has now moved from an interesting automation concept into a cleared medical product. Its next test will be much more conventional: whether enough laboratories will pay for software that saves specialist time, and whether equipment manufacturers see enough value to make that software part of their own offering.