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SIBIONICS präsentiert den GS3 in Melbourne und treibt damit eine effizientere, KI-gestützte Glukoseüberwachung voran

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  • APAC - English
  • USA - español

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SIBIONICS

Aug 31, 2026, 07:05 ET

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MELBOURNE, Australien, 31. August 2026 /PRNewswire/ -- SIBIONICS präsentierte seine Sensorinnovation und die KI-gestützte Glukoseüberwachung auf dem gemeinsamen Kongress von IDF-WPR, ADC und Metabolic Diseases 2026, der vom 18. bis 21. August in Melbourne stattfand. Durch den Stand Nr. 1, ein wissenschaftliches Symposium und Interviews vor Ort mit zertifizierten Diabetesberatern (CDEs) führte das Unternehmen fortschrittliche Technologie, klinische Evidenz und Perspektiven aus der Praxis zusammen.

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At IDF-WPR 2026 & ADC 2026 & Metabolic Diseases 2026, we shared how GS3 is bringing AI into everyday glucose management — from easier meal logging and food analysis to smarter insights into glucose trends.
At IDF-WPR 2026 & ADC 2026 & Metabolic Diseases 2026, we shared how GS3 is bringing AI into everyday glucose management — from easier meal logging and food analysis to smarter insights into glucose trends.
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Die technologische Geschichte hinter dem GS3 reicht weit über die Glukoseüberwachung hinaus. Die Arbeit von SIBIONICS im Bereich der Gehirn-Computer-Schnittstellen umfasst eine Netzhautprothese, die darauf ausgelegt ist, Menschen mit schwerem Sehverlust infolge degenerativer Erkrankungen der äußeren Netzhaut – wie etwa Retinitis pigmentosa – eine eingeschränkte visuelle Wahrnehmung zu ermöglichen. Diese äußerst komplexen Systeme erfordern eine präzise, stabile Biosensorik und eine robuste Signalverarbeitung. SIBIONICS hat diese hochspezialisierte Technik in eine breiter zugängliche Medizintechnik umgesetzt: kontinuierliche Glukoseüberwachung. Dieselbe Plattformfunktion unterstützt nun den GS3 – einen ab Werk kalibrierten 14-Tage-CGM-Sensor mit einem Profil von 2,9 mm, der für eine zuverlässige Überwachung bei geringer Belastung für den Anwender entwickelt wurde.

Auf dem Symposium „Beyond Glucose: The Integrated Future of CGM, CKM, and AI in Diabetes", das gemeinsam von SIBIONICS und Air Liquide Healthcare ausgerichtet wurde und dessen Sitzungsvorsitzender Professor Sofianos Andrikopoulos, Vorstandsvorsitzender der Australian Diabetes Society, war, wurden drei Perspektiven zusammengebracht. Professor David O'Neal von der Universität Melbourne und stellvertretender Direktor des Australian Centre for Accelerating Diabetes Innovations hat die neuesten klinischen Erkenntnisse zur kontinuierlichen Glukose- und Ketonüberwachung ausgewertet. Shannon Lin, außerordentliche Professorin und Spezialistin für Diabetes und Ernährung an der University of Technology Sydney, untersuchte, wie CGM über die bloße Datentransparenz hinaus zu einer personalisierten, vorausschauenden und umsetzbaren Unterstützung führen kann. Professor Wei Qiang, stellvertretender Chefarzt und stellvertretender Direktor der Abteilung für Endokrinologie und Stoffwechsel am Ersten Angeschlossenen Krankenhaus der Xi'an Jiaotong University, skizzierte ein integriertes, KI-gestütztes Ökosystem, das zuverlässige Sensorik, Kontext und Lernen miteinander verbindet.

Während des gesamten Kongresses besuchten Ärzte und Diabetesberater den Stand von SIBIONICS, um GS3 kennenzulernen und dessen Funktionen zum Glukosemangement zu erörtern. In anonymisierten Interviews beschrieben die Diabetesberater den Sensor als klein, leicht, bequem und einfach einzurichten. Sie sahen besonderes Potenzial in der KI-gestützten Erkennung von Glukosespitzen, der vereinfachten Protokollierung von Mahlzeiten und der Lebensmittelanalyse, die Glukosetrends mit dem Mahlzeitkontext verknüpft. Ihr Feedback unterstrich zudem die Bedeutung von Personalisierung, klaren Kohlenhydratschätzungen und klinisch nützlichen Ereigniszeitachsen – was bekräftigt, dass KI die Aufklärung und Entscheidungsunterstützung erweitern, nicht aber die professionelle Versorgung ersetzen sollte.

Mit Blick auf die Zukunft plant SIBIONICS, seine Sensorplattform mit kontinuierlicher Ketonüberwachung, Insulinabgabe, KI und anderen Diabetes-Technologien zu integrieren. Das Ziel ist ein umfassenderes, zuverlässiges und effizientes Ökosystem, das den Weg von den Daten zum Verständnis – und vom Verständnis zum Handeln – verkürzt.

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