AI and Medical Devices – General guidance principles for SMEs to meet the regulatory demands on safety and efficacy in the EU in order to reach the market

Abstract: Artificial intelligence (AI) is the study of science, engineering, and the development of intelligent machines. AI is based on human intelligence with the exception that it is not restricted by biologically observable limitations. AI has developed rapidly over the past few years and has become important all over the world. This Master’s thesis brings up AI as a medical device and the European market. The thesis provides guidance in the form of important aspects to be considered by small and medium-sized enterprises (SMEs) when marketing products in Europe. There is a lack of guidance and clear descriptions regarding AI/ML-based medical devices in Europe. Both MDR and medical devices with AI/ML are relatively new and uncharted. There are no clear guidelines, instructions, or articles that clearly describe what is needed to get an AI/ML-based medical device on the European market. In summary, there is no guidance that SMEs could benefit from when it comes to AI/ML-based medical devices and the European market. With this thesis the subject is enlightened and hopefully, the gap in knowledge about this is reduced. The chosen method to achieve the goal of this thesis is both a literature review and qualitative research in the form of interviews with relevant experts within the field. The results show that there is a lack of guidelines and regulations for AI-based medical devices, it is harder for SMEs to market such devices and it is complicated to put an AI-based medical device on the European market due to MDR. SMEs should consider certain aspects important when developing an AI/ML-based medical device and placing it on the European market. The identified aspects are creating a regulatory plan, using guidelines from example FDA, procuring regulatory competence from the start, risk classification, economics, clinical evaluation, risk management, having end-user in mind during the development, and data management/cybersecurity. The results also show that if guidelines are developed, they should contain thresholds for different characteristics in AI/ML-based medical devices, risk classification of the device, classification requirements, checklists, templates, actions, good manufacturing process description, data management, cybersecurity, patient safety process description, clinical evaluation process description, regional regulatory adaptions, and risk mitigation. The results of this thesis can be used in many ways and by many. By solely using this report for AI/ML-based medical devices, complete compliance with MDR is not fulfilled.