ClinMed 2024 Abstracts


Area 1 - ClinMed

Full Papers
Paper Nr: 5
Title:

An Example of Personalized Pathway in Medical Device Evaluation for a Master Student in Clinical Research

Authors:

Guy Carrault, Thierry Chevalier, Bruno Laviolle, Lionel Pazart and Sylvia Pelayo

Abstract: The aim of this paper is to explore the possibility of combining several training lessons to offer students a personalized pathway in the field of medical device regulation. Feasibility is demonstrated through an experiment currently being conducted between the universities of France-Comte, Lille, Montpellier and Rennes.
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Paper Nr: 6
Title:

Promote Competency-Based Training Approach in Quality, Regulatory and Clinical Affairs to Improve MD/IVDD Safety and Performance

Authors:

Lionel Pazart, Vincent Armbruster, Debora Monin, Corinne Delorme, Monique Borel, Damien L. Nihouannen, Frédéric Barbot, Fabrice Bouquet, Guy Carrault, Thomas Lihoreau, Marlène Durand, Helène Clogenson and Sylvia Pelayo

Abstract: The aim of this paper is to analyze the training needs introduced by the implementation of the European regulations on medical devices (MDR) and in vitro diagnostic medical devices (IVDR), and to analyze the appropriateness of a competency-based training approach. Finally, a number of ideas are put forward concerning certain topics to be addressed in a Europe-wide approach.
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Paper Nr: 7
Title:

Clinical Evaluation of Collaborative Artificial Intelligence Systems: Lessons from the Case of Robot-Assisted Surgery

Authors:

Alexandre Coste, Frédéric Barbot and Thierry Chevalier

Abstract: Collaborative AI systems, which combine both forms of intelligence (i.e., human and machine), are attracting increasing interest from the scientific and medical communities, with various applications in radiology (clinical decision support systems) and surgery (robot-assisted surgery). However, despite their promise, these systems face significant challenges in integrating into clinical practice due to a lack of transparency, trust, and clinical validation. Drawing on the case of robotic surgery, the aim of this work was to analyse the scientific evidence for ten surgical robots currently on the market (i.e., CE-marked or FDA-cleared/approved) that meet the definition of a collaborative AI system. We found a low number of peer-reviewed publications and a lack of transparency from authors and manufacturers, particularly regarding the functioning of their devices, which are often considered as ‘black boxes’. Furthermore, the term ‘artificial intelligence’ is under-utilised in scientific publications, regulatory submissions, and commercial materials. Based on these findings, we propose three recommendations to promote the integration of these medical devices: 1) promote the transparency, explainability, and comprehensibility of AI devices by encouraging manufacturers to provide more detailed information about their systems and their functioning, including the interrelationship with the user; 2) promote randomised controlled multicentre trials to provide stronger evidence on the performance and safety of these devices; 3) encourage the publication of scientific results in peer-reviewed journals to expose them to scientific scrutiny and improve transparency. These recommendations have been carefully formulated to cover a wide range of AI/ML-enabled medical devices, beyond the case of surgical robots reviewed here.
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Paper Nr: 9
Title:

A Skill based Educational Program for Future Regulatory Affairs Professionals in the Medical Devices Industry: A Top down Approach at Polytech Lyon University, France

Authors:

Norbert Noury, Emmanuel Perrin and Claire Gaillard

Abstract: The Medical devices industry is facing a shortage in the professionals in Regulation Affairs who are in charge with the regulation steps to bring their MD to the market. The Master ATRDM at Polytech Lyon 1 University, France, was elaborated following a top-down approach based on the development of competencies of the learners, with an agile iterative process to update the contents.
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Paper Nr: 11
Title:

Use of a Digital Positioning and Categorisation Aid for Clinical Investigations on Medical Devices: Questioning the Complexity of the Field and Harmonizing Stakeholders' Understanding

Authors:

Jean-Baptiste Pretalli, Stéphanie Py, Fatimata S. Sall, Magali Nicolier, Karine Charrière, Thierry Chevallier and Thomas Lihoreau

Abstract: Medical devices must comply with the safety and performance requirements of the European Medical Device Regulation. For clinical investigations, regulatory approval from competent authorities is required. ICTROUVE is a digital tool designed to help identify the clinical investigation’s category when applying to the French competent authority, the Agence Nationale de Sécurité du Médicament et des produits de santé (ANSM). We aimed to evaluate ICTROUVE and to prepare a larger-scale study. This pilot study was divided in two sequences. The aim of the first was to recruit experts and to collect study synopses for which the clinical investigation’s category issued by the ANSM was known. To achieve this aim, we created and sent a questionnaire to researchers and regulatory managers via the Tech4Health network. During the second sequence, the experts had to read the synopses and assign them a clinical investigation’s category, first without and then with the help of ICTROUVE. A satisfaction questionnaire was then completed. We found a low decision agreement between experts and ANSM (39% without ICTROUVE, 51.7% with). ICTROUVE was perceived as useful, easy and quick to use. Information was gathered to facilitate a larger-scale evaluation, notably on the collection of synopses and the search for experts..
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