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SUMMARY:Clinical Evaluation for AI-Enabled Medical Device
DESCRIPTION:Navigating Clinical Evidence in the Age of AI\nDate: 14 October 2026 | Time: 17:00 CET / 16:00 GMTFormat: Online Webinar \nAI-enabled medical devices are reshaping the way we approach clinical evaluation. \nFrom defining sufficient clinical evidence to addressing bias\, generalisability\, evolving algorithms and real-world performance\, these technologies bring new questions and challenges for medical device professionals. \nJoin ICEPS for an interactive webinar exploring how established clinical evaluation principles can be applied to AI-enabled medical devices — and where new approaches may be needed. \nWith perspectives from across the medical device ecosystem\, the session will combine expert discussion with the opportunity for participants to ask their questions directly to the panel. \nWhat We’ll Discuss\nDuring the webinar\, we’ll explore questions such as: \n\nWhat does sufficient clinical evidence look like for an AI-enabled device?\nHow should bias and generalisability be addressed?\nWhen might a prospective clinical investigation be needed?\nHow should we approach evolving algorithms and real-world performance?\nWhat role should post-market clinical evidence play?\n\nThese topics reflect the main clinical evidence challenges identified for the webinar. \nSpeakers:\nDr. Kimberly Peven\nClinical Lead\, Regulatory and Clinical Evaluation Specialist\, Internal Clinical Scarlet – Scarlet \nKimberly Peven leads the clinical team at Scarlet\, where she works to help bring safe AI medical devices smoothly through the regulatory process and into the hands of patients. With a background as a Registered Nurse and a PhD in Epidemiology\, she has spent much of her career focused on women’s health\, spanning academic research\, policy work\, and healthtech. She cares deeply about ensuring emerging medical technologies are grounded in solid and continued clinical evidence. \nProf. Dr. Stephen Gilber\nProfessor – Technische Universitat Dresden \nProf. Dr. Gilbert worked in senior MedTech and Digital Heath roles for 5 years\, before returning to academia in 2022 in Dresden\, Germany as Europe’s first full Professor of AI Medical Device Regulatory Science. His research goals are the advancement of regulatory science in AI-enabled medical devices. Innovative digital approaches in healthcare must be accompanied by innovative regulatory and oversight approaches to ensure speed to market\, to maximise the access of patients to life saving treatments while at the same ensuring safety. He evaluates existing methods and regulatory frameworks and develops new solutions for the oversight of AI and digital health. \nAnkeet Tanne\nSenior Consultant – Hardian Health \nAnkeet is a medical doctor with previous experience developing machine learning tools for the prediction of neurodegenerative diseases. He is a Senior Consultant at Hardian\, where he leads the Clinical Department and has successfully advised several clients on product strategy\, and clinical strategy for obtaining CE marking and FDA clearances. Hardian’s core focus is advising companies who are developing novel Software and AI medical devices\, to help them enter international markets. \nModarator\nAmie Smirthwaite\n \nAmie Smirthwaite is a clinical and regulatory affairs expert with over 30 years’ postdoctoral experience in medical devices spanning new product development\, quality and regulatory systems\, and clinical evidence. She has been involved in the development of several MDCG and other clinical evaluation guidance documents and has served on numerous advisory board positions\, including CORE-MD\, HEU-EFS\, and NORE\, amongst others. She is an active participant in several ISO committees relating to medical device clinical and technical evidence. She currently works as an independent consultant advising on clinical and regulatory affairs\, but previously worked for BSI\, where she was Global Head of Clinical Compliance. Amie was BSI’s first Head of Clinical Compliance\, building their clinical compliance team and leading the development of their clinical evaluation processes. She also developed extensive training materials while at BSI\, including clinical evaluation\, technical documentation\, risk management\, ISO 13485\, EU MDR\, and biological evaluation. Amie is a Fellow of the Regulatory Affairs Professional Society \nWho Should Attend?\nThis webinar is designed for professionals working across Clinical\, Regulatory\, Quality\, R&D and Medical Affairs\, as well as manufacturers\, CROs and consultants involved in the development or evaluation of AI-enabled medical devices. \nWhether you’re new to AI-enabled devices or already working in the field\, this webinar is an opportunity to hear different perspectives\, explore evolving expectations and bring your own questions to the discussion. \nHave questions about clinical evaluation for AI-enabled medical devices?\nBring them to the webinar and join the conversation. \nPractical Information\n\nDate: 14 October 2026\nTime: 17:00 CET / 16:00 GMT\nDuration: 60 minutes\nFormat: Online via Zoom\nRegistration Fee: Free for ICEPS members and 35€ for non-members (VAT excl.)\nZoom Access: The Zoom link and connection details will be sent by email.\nRecording: The session will be recorded\, and access to it will be only for ICEPS members.\n\nImportant Information\nPlease note that this event is a webinar only. \nParticipants will have the opportunity to ask questions and exchange directly with the expert speaker. \nThis session is not a training course\, and participation does not provide a certificate of attendance\, training completion\, or certification. \nYour Zoom access link is personal and may not be shared. Any participant not registered through ICEPS may be removed from the webinar without notice. \nThe session is recorded and only available for ICEPS members. \n 
URL:https://iceps-mdivd.org/event/clinical-evaluation-for-ai-enabled-medical-device/
LOCATION:Zoom  Webinar
ATTACH;FMTTYPE=image/jpeg:https://iceps-mdivd.org/wp-content/uploads/2026/08/261014-Clinical-Evaluations-for-AI-driven-Medical-Devices_web.jpg
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