Artificial intelligence in medical device software and high-risk medical devices – a review of definitions, expert recommendations and regulatory initiatives

ABSTRACT

Introduction

Artificial intelligence (AI) encompasses a wide range of algorithms with risks when used to support decisions about diagnosis or treatment, so professional and regulatory bodies are recommending how they should be managed.

Areas covered

AI systems may qualify as standalone medical device software (MDSW) or be embedded within a medical device. Within the European Union (EU) AI software must undergo a conformity assessment procedure to be approved as a medical device. The draft EU Regulation on AI proposes rules that will apply across industry sectors, while for devices the Medical Device Regulation also applies. In the CORE-MD project (Coordinating Research and Evidence for Medical Devices), we have surveyed definitions and summarize initiatives made by professional consensus groups, regulators, and standardization bodies.

Expert opinion

The level of clinical evidence required should be determined according to each application and to legal and methodological factors that contribute to risk, including accountability, transparency, and interpretability. EU guidance for MDSW based on international recommendations does not yet describe the clinical evidence needed for medical AI software. Regulators, notified bodies, manufacturers, clinicians and patients would all benefit from common standards for the clinical evaluation of high-risk AI applications and transparency of their evidence and performance.

KEYWORDS:

• Artificial intelligence
• evidence-based medicine
• machine learning
• medical devices
• professional consensus recommendations
• standards
• regulations
• EU medical device regulation

Acknowledgments

We thank Paul Piscoi and Nada Alkhayat, Unit D3, DG SANTE, European Commission for their advice, Piotr Szymanski for his suggestions, and Yijun Ren for help in accessing the documents of the NMPA.

Declarations of interest

AGF is Chairman of the Regulatory Affairs Committee of the Biomedical Alliance in Europe, and Scientific Coordinator of the CORE-MD consortium; he attends the Clinical Investigation and Evaluation Working Group of MDCG. He has no financial conflicts of interest. EC has received honoraria as consultant or as speaker from Medtronic, Daiki-Sankyo, and Novartis. KC is an employee of Koninklijke Philips N.V.; he is Chair of the Software Focus Group at COCIR and DITTA, and delegate to the IMDRF working groups on Software as a Medical Device and AI-based Medical Devices. He is a Belgian expert member contributing to international standards committees at IEC/TC62 Electrical equipment in medical practice, ISO/TC215 Health Informatics, ISO/TC210 Quality management, ISO/IEC JTC 1/SC 42 Artificial Intelligence, and CEN/CENELEC JTC21 Artificial Intelligence. RHD has share options in Mycardium.AI. SHG declares no non-financial interests; he is an advisor/consultant for Ada Health GmbH and holds share options; and he has consulted for Una Health GmbH, Lindus Health Ltd. and Thymia Ltd. LH is an employee of Elekta; he is chair of the clinical committees of COCIR and DITTA; industry stakeholder at IMDRF working groups on Clinical Investigation, Evaluation, PMCF and IVD Performance Evaluation; industry stakeholder at ISPOR (WHO) Health Technology Assessment; and industry stakeholder at the MDCG Working Groups on Clinical Investigation & Evaluation, and Borderline and Classification (Software and Risk Classification). GMcG is a member of the Medical Device Coordination Group (MDCG) working group on Clinical Investigation and Evaluation (CIE), and of the International Standardization Organisation (ISO) technical committee for implants for surgery (ISO/TC 150). GO’C is a member of the Clinical Investigation and Evaluation subgroup of MDCG. ZK is an employee of Dedalus HealthCare GmbH and represented industry in European Task Force on Clinical Evaluation of MDSW (MDCG2020-1). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewers disclosure

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Additional information

Funding

This work was supported by grant 965246 from the European Union Horizon 2020 Research and Innovation Programme, for the CORE–MD project (Coordinating Research and Evidence for Medical Devices).