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Artificial intelligence is rapidly transforming the life sciences sector — and its impact on the medical devices industry is particularly significant, especially after the coming into force of the EU AI Act. From diagnostics to patient monitoring and personalized treatments, AI-powered medical technologies are reshaping the future of healthcare in Italy, Europe, and globally. But as innovation accelerates, so does the need for a robust legal framework — especially under the recently adopted AI Act.
In this article, we explore how AI is being integrated into medical devices, the regulatory implications of the AI Act, and why compliance is becoming just as critical as innovation.
Why Artificial Intelligence Matters in the Life Sciences Sector
Artificial intelligence is already unlocking game-changing applications in healthcare. It can analyze vast datasets, recognize patterns, and generate predictive insights that were previously impossible to obtain in real time. From supporting R&D in drug development to revolutionizing the design and functionality of medical devices, AI is now central to the evolution of health systems.
While only a fraction of generated data is currently used to improve care, healthcare organizations and manufacturers are increasingly turning to AI to:
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Enhance diagnostic accuracy
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Reduce clinical and human error
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Monitor patients in real time
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Support personalized treatment pathways
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Optimize resource allocation across hospitals and clinics
The benefits are not just theoretical. AI-driven devices are already contributing to earlier cancer detection, real-time glucose monitoring, and reduced hospital readmissions through remote patient management.
Medical Devices and AI: The Legal Intersection with the AI Act
The convergence of artificial intelligence and medical devices is now under direct scrutiny from EU lawmakers. Under the AI Act (Regulation (EU) 2024/1689), most software classified as a medical device is deemed a “high-risk AI system.” This includes, for instance, AI models embedded in diagnostic imaging platforms, decision-support tools, or remote monitoring systems.
What does this mean in practice?
Manufacturers must now comply with both:
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Medical Device Regulation (EU) 2017/745 (MDR) or In Vitro Diagnostic Regulation (IVDR), and
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The AI Act’s requirements on risk management, transparency, data quality, and human oversight.
This dual compliance path involves a conformity assessment that encompasses both medical and AI-specific evaluations. However, guidance from regulators remains limited. Notified Bodies will need to broaden their expertise, and companies may face delays similar to those experienced during the transition to MDR and IVDR.
Key Legal Uncertainties Around the AI Act in the Life Sciences Sector
1. Research & Development Exemption
Article 2(6) of the AI Act excludes AI systems developed solely for scientific research and development. But how this applies to pharmaceutical R&D remains debated. While some stakeholders argue for a broad exemption, regulators currently lean toward a narrow interpretation. Pending official guidance, companies should carefully evaluate whether their AI tools fall within or outside this scope.
2. Conformity Assessment Bottlenecks
The classification of many AI medical devices as “high-risk” triggers a comprehensive conformity assessment, yet Notified Bodies lack clear standards or checklists for evaluating AI-specific criteria. This may slow time-to-market for innovative solutions.
3. Privacy and Data Protection
AI-powered medical devices process sensitive health data and must fully comply with the GDPR. Developers must implement strong safeguards and conduct AI-specific impact assessments that consider the rights and freedoms of data subjects. The use of anonymized or pseudonymized data, where feasible, is encouraged to reduce risk.
Opportunities Ahead: Digital Twins and Predictive Algorithms
One of the most promising AI use cases is the development of digital twins — virtual models that simulate how real patients respond to treatments. These in silico methods could significantly reduce reliance on animal and human trials. Initiatives like the European Virtual Human Twins and EDITH project aim to provide platforms for safe and ethical implementation of such models, emphasizing compliance with the AI Act, GDPR, and cybersecurity standards.
Moreover, intelligent sensors embedded in AI medical devices can deliver hyper-personalized care by adapting to individual patient needs in real time. This is particularly relevant in areas like chronic disease management, where proactive interventions can prevent emergencies and reduce healthcare costs.
Barriers to Adoption of AI in Medical Devices
Despite the potential, the road to widespread implementation is not without obstacles:
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Data fragmentation and lack of interoperability hamper the full utilization of health data. The forthcoming European Health Data Space may improve data access and standardization.
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Trust and digital literacy remain low among both patients and healthcare professionals. Investing in training and communication is key to building confidence in AI-powered care.
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Regulatory fragmentation continues to create legal uncertainty, especially in cross-border research and product deployment across EU member states.
Looking Forward: A Human-Centered Approach to AI in Healthcare
Artificial intelligence is no longer a futuristic concept — it is a present-day catalyst for improving medical devices and saving lives. With the AI Act laying the legal foundation, Europe has the chance to lead globally in ethical and responsible AI deployment in life sciences.
But regulation is only part of the equation. Developers, manufacturers, hospitals, and regulators must work together to ensure that innovation serves patients — not the other way around.
When combined with robust legal safeguards and ethical design, AI-enabled medical devices have the potential to revolutionize modern medicine. They can make care more accurate, efficient, and equitable — and in doing so, redefine the future of healthcare.
On the topic, read DLA Piper’s AI Law Journal available HERE and other articles on the topic available HERE.
Authors: Nicola Landolfi, Roxana Smeria and Nadia Feola.