Elekta

Introduction

Artificial intelligence (AI) has huge potential improving healthcare using the vast amounts of clinical data. AI software algorithms can use real-world data to support better health care decisions or improve performance and safety of medical devices. Manufacturers have embedded AI technology into various applications such as imaging, laboratory testing, patient monitoring, personalised apps and robotics.

AI also presents unique challenges due to its complexity and the iterative and data-driven nature of its development. This triggered the delopment of the European Union AI Act and the development in the US, Canada and the UK of the Good Machine Learning Practices.

European Union AI Act

The European Union AI Act (EU-AIA) is aimed at covering AI in general. The structure of the Medical Device Regulation (MDR) was used as blue print for the EU-AIA. This is very pleasant, since it makes the EU-AIA easy to understand. The MDR includes requirements on risk management, conformity assessment by notified bodies, post-market surveillance and a vigilance system. Those elements can also be found in the EU-AIA.

The EU-AIA however has substantial changes when compared to MDR. The MDR focusses on treating individual patients with safe and performing medical devices. The EUAIA focusses on protecting the population from AI solutions. The goals are incompetible and maybe even conflicting, so the substantial changes are logical.

The incompatible requirements are a significant barrier for high quality AI-based medical devices being placed on the EU market. The EU-AIA changed concepts for risk management and did not define risk. EU-AIA risks for fundamental rights conflict with MDR patient safety risks, potentially making medical devices unsafe. The EU-AIA also defined provider, user, importer and putting into service differently than the MDR.

“The MDR Focuses On Treating Individual Patients With Safe And Performing Medical Devices. The EUAIA Focuses On Protecting The Population From AI Solutions.”

Medical device manufacturers also often lack direct access to training data because of patients rights, but authorities in the EU-AIA need to be granted direct access to patient training data. In addition datasets for the EU-AIA need to be error free and complete, however for medical devices testing data is used to check the quality of AI clinical data.

The list of inconsistencies and duplications is very long, creating legal uncertainty, increasing costs and potentially blocking market access. Most software medical devices are within the scope of the EU-AIA, not only the AI-based medical devices. The EU-AIA will have an adverse effect on the availability of (AI-based) software medical devices, which cannot be the purpose of the act.

Availability in 2022 of medical devices is already endangered since less then 20% of the devices have been transferred from the AIMDD and MDD to the MDR. The administrative burden and unclarity of requirements of the MDR play a major role. The proposed EU-AIA can make an unacceptable situation worse for the European patient. Currently most AI-based medical devices are placed first on the USA market and it is questionable if they will reach the EU market.

When the MDR is removed from the EU-AIA annex II section A, then most inconsistencies and duplications are removed. AI-based medical devices are already in great detail regulated under the MDR. The European Commission has a scientific workgroup CORE-MD investigating what additional requirements are needed for AI-based medical devices under the MDR.

Good Machine Learning Practices

The FDA, Health Canada, and the UK MHRA have published Good Machine Learning Practices (GMLP) that can be used to develop AI medical devices. The goal of Good Machine Learning Practices is to promote safe, effective, and highquality medical devices that use artificial intelligence and machine learning. The 10 practices identify areas where the International Medical Device Regulators Forum (IMDRF) and international standards organizations could work to advance GMLP. The guiding practices can also be used to develop MDCG guidance for the EU-MDR, instead of using the EU-AIA.

The guiding practices are shown in the table. Each guiding practice has explanation in the related publication on how to apply it. Guiding practices 1, 2, 5, 6, 9 are straightforward, logical and good implementable advise. Guiding practice 3 makes sense, however might be in conflict with the EU-AIA. Guiding practice 4 seems logical, but might need adoption for rare diseases where only small data sets are available. Guiding practice 7, 8 and 10 deserve special attention form manufacturers and users, since they cause regular issues in practice.

The MDR uses additional concepts to the GMLP such as benefits need to outweigh the risks, the medical device needs to be state of the art, and clinical evidence need to be available. However these concepts are already part of the MDR requirements. 

Conclusion

The EU-AIA makes it difficult or impossible for good AI-based medical devices to be placed on the EU market. The EU-AIA should be fully consistent with the MDR. This is most easily achieved, by not including the MDR in EU-AIA annex II section A, but by including the requirements of the EU-AIA in MDR MDCG guidance.

Recently the USA has become the preferred location to place AI-based medical devices on the market, because of the complexities of the MDR. The additional complexity introduced by the EU-AIA will accelerate this development. There will be less choice and delayed access to crucial digital health innovation for European patients and healthcare professionals, which cannot be the purpose of the EU-AIA.

Biography

Leo Hovestadt is involved with developing and implementing medical device regulations and guidance, starting with the Active Implantable Medical Device Directive 30 years ago. Leo is the author of the recent MDR Guide for Medical Device Software, and is a regular key note speaker on topics like medical device clinical evidence, artificial intelligence and digital health. He is the Director Quality & Regulatory of Elekta, a radiation therapy medical device company.