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AI In EU MedTech: Regulatory Challenges And Solutions

A few weeks ago, MedTech Europe published an extensive report on how Artificial Intelligence (AI) may improve the malfunctioning healthcare system in Europe and outlined the major challenges to adopting the new healthcare technologies on the continent. 

Covid-19 Showing Weaknesses Of The EU Healthcare

The Covid-19 crisis has blatantly shown the inadequacies of the European healthcare system and the need for a change and upgraded technology that will facilitate the issues the outdated system is struggling with. In recent years, the amount of technology that can assist in more efficient MedTech has grown immensely.

MedTech Startups In Europe Receiving Gigantic Funding In 2020

Only during the pandemics, MedTech startups in Europe have been the undoubted winner, managing to get approximately $3 billion in funding, as compared to the approximate $40 billion that all European startups received in 2020. Although AI presents huge opportunities in several aspects of healthcare, MedTech’s report shows that the regulatory, legal, social, and technical challenges that delay and prevent effective incorporation of AI into the European healthcare system. 

AI Solving Most Pressing Issues For European Healthcare

“Artificial Intelligence in healthcare can solve pressing challenges for European healthcare systems, but there are critical barriers that need to be addressed,” Michael Strübin, the Director Digital Health at MedTech Europe, said. “ “With this report, we want to highlight what the benefits are if we succeed, for patients, healthcare professionals and for society as a whole.”

The study focused on eight different categories of AI applications:  wearables, imaging, laboratory applications, physiological monitoring, real-world data, virtual health assistance, personalized apps, and robotics.

The key estimates of the research showed that: 

  • Annually, AI could contribute to saving 400, 000 lives in Europe 

  • Annually, the European healthcare system could save up to 200 billion euros because of the AI facilitation 

  • Annually, The medical staff that has been in shortages for years across Europe could save up to 1,8 billion hours.

Barriers To AI Adoption By European MedTech

However, while it all sounds wonderful, there are several barriers and limitations that must be addressed before European MedTech will be ready for the adoption of AI. A large number of challenges are connected to the specific, sensitive nature of healthcare data and the risks accompanied by the distrust of the citizens.

The digital health devices and IoT devices are able to generate massive amounts of data. The issue is, however, with the fact that the data is not always structured. It also regularly does not meet the standards of the highest quality. Thus, it can not be translated into clinical practice. Another issue is the sensitivity of data. Healthcare data is highly personal, sensitive, and complex, thus, it must be protected by the strictest privacy and data protection rules.

MedTech Europe describes in detail the most common challenges alongside the possible solutions:

Legal Challenges:

Currently, the legal framework that regulates AI in healthcare are the following: 

− In Vitro Diagnostic Regulation VI & Medical Device Regulation VII (IVDR/MDR) 

− General Data Protection Regulationviii (GDPR)

− National advertising and promotion laws

− Product Liability Directive ix 

− Existing industry code x  

Of course, which particular framework will apply depends on the specific case and technology to be used. However, AI is such a broad and complex field that it does not always fit into the existing regulatory framework or are being limited due to the application of an insufficient amount of regulatory bodies. Thus, the European Union should revise the regulation in order to ensure that the legal framework does not impede the AI’s development.

Technical Challenges:

As described above, health data is fragmented and frequently does not meet sufficient quality. It is also stored in different places by many different actors. The healthcare industry in Europe has not yet achieved the goal of creating a universal, shared healthcare database. The formation of a European Health Data Space could provide alignment across the European Countries. 

Cybersecurity Challenges:

Even the biggest, supposedly most-secure cybersecurity giants can be vulnerable to cyber-attacks. Thus, MedTech can also be vulnerable to the same risks which constitutes a big issue. The only sensible solution here is efficient, mutual collaboration of government, EU, manufacturers, and health providers that can build a bulletproof framework to be adopted across the European healthcare ecosystem. 

Social Challenges:

Finally, there are the social challenges. One may argue that social challenges will be the ones constituting the biggest threat. Citizens, patients, healthcare providers, hospital staff, professionals all can be doubtful about incorporating AI. And while technology develops and disrupts the long-standing industries at an unprecedented pace, it takes way longer to change the fundamental beliefs of the population. Moreover, even the professionals who are embracing AI incorporation are currently not trained or prepared to work with this type of technology. The solution proposed by MedTech Europe is investing in extensive education and training for professionals first. Simultaneously, the steps to educate the patients and citizens should take place. 

The CEO of MedTech Europe, Serge Bernasconi said, “Artificial Intelligence can address many healthcare challenges and the EU has the potential to lead this area by building an advanced regulatory environment, enabling trustworthy AI, and ensuring greater patient trust.”

The main recommendations of MedTech Europe include: 

  • Building data and infrastructure for AI 
  • Establishing a strong governance framework 
  • Equipping the workforce with the necessary skills 
  • Funding for AI 


Nel Tomczyk
Nel Tomczyk
Nel is a writer for RegTech Global. From her past experience, she gained a deep understanding of fintech, AI, regulations, and new technologies. She has vast experience in journalism and entrepreneurship.


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