Median Technologies to Host Key Opinion Leader (KOL) Webinar on AI and Lung Cancer Screening

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Webinar to focus on the eyonis? Lung Cancer Screening (LCS) REALITY data
November 7, 2024 – 1:30 pm CET / 7:30 am ET – Registration link

SOPHIA-ANTIPOLIS, France, October 30, 2024--(BUSINESS WIRE)--Regulatory News:

Median Technologies (FR0011049824, ALMDT, PEA/SME eligible, "Median" or "The Company"), a leading developer of eyonis?, a suite of artificial intelligence (AI) powered Software as a Medical Device (SaMD) for early cancer diagnostics, and a globally leading provider of AI analyses and imaging services for oncology drug developers, today announced that it will host on November 7, 2024 at 1:30 pm CET / 7:30 am ET a KOL webinar to discuss REALITY, the recently completed study of the eyonis? LCS SaMD for early diagnosis of lung cancer.

Two leading U.S. pulmonology experts Prof. Anil Vachani, from the Hospital of the University of Pennsylvania, and Prof. Javier Zulueta, from the Icahn School of Medicine at Mt Sinai, will share their views on the data from REALITY and how eyonis? LCS may impact lung cancer early diagnostics.

Final results from REALITY, the first of the two pivotal studies for the eyonis? LCS SaMD, which will be included in filings for marketing authorizations in the US and in Europe in H1 2025 also will be presented by Fredrik Brag, CEO and founder of Median Technologies.

Large epidemiologic studies conducted in the US and in Europe have shown that Low-Dose Computed Tomography (LDCT) lung cancer screening enables diagnosis of lung cancer at the earliest stage of the disease, when patients can be cured. However, the challenge of interpreting LCS images is a significant burden for medical professionals, especially when diagnostic imaging data are inconclusive, close to the current technological limit of detection. Ordering confirmatory procedures to investigate inconclusive diagnostic imaging data, like biopsies, which are invasive and expose patients to potential risks, presents ethical and financial burdens for doctors, patients and payers.

"Improving diagnosis accuracy and efficiency to facilitate broader adoption of lung cancer screening procedures is an unmet medical challenge that AI technology is well-suited to address. Radiologists can be burdened by LCS data, especially when it’s inconclusive. Our topline REALITY study data reported in August suggest that eyonis? LCS may well be a game changer, helping doctors accurately detect more lung cancer cases early enough to save lives while also increasing screening capacity to catalyze broad adoption of lung cancer screening programs in the US and elsewhere. We look forward to discussing these data with the globally recognized pulmonology experts," said Fredrik Brag.