Regulating the future of laboratory medicine: European regulatory landscape of AI-driven medical device software in laboratory medicine

Artificial intelligence (AI) is rapidly transforming laboratory medicine, impacting medical devices and healthcare practices. Despite these advancements, AI-based medical device software (MDSW) introduces a new layer of complexity in regulatory compliance. This paper outlines the regulatory landscape for MDSW and AI-driven MDSW, clarifying the responsibilities of laboratory professionals and manufacturers under the <i>In Vitro</i> Diagnostic Regulation (IVDR), ISO 15189:2022, and the Artificial Intelligence Act. An analysis of 89 MDSWs approved under the IVDR, derived from the European Database on Medical Devices (EUDAMED) reveals a diverse landscape of applications, ranging from digital pathology and molecular diagnostics to laboratory automation and clinical decision support. While Germany currently dominates the EU market for these devices, and the majority of approved MDSW remain non-AI driven and classified as low-risk, the increasing presence of AI-powered Class C devices underscores the growing potential of software in complex diagnostic scenarios. However, realizing the full potential of AI in laboratory medicine requires careful navigation of the evolving regulatory landscape. Key challenges persist, including defining intended use, ensuring robust clinical evidence, mitigating data bias, and establishing rigorous post-market surveillance. Balancing regulatory oversight with innovation is critical to fostering the development of trustworthy AI systems without stifling progress. As regulatory frameworks continue to evolve, establishing clear validation methodologies and transparent compliance pathways will be essential to unlocking the full potential of AI in laboratory medicine while ensuring the highest standards of safety and clinical effectiveness.

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Publication Details

Journal
Clinical Chemistry and Laboratory Medicine (CCLM)
Published
2025-05-27
DOI
https://doi.org/10.1515/cclm-2025-0482
Citations
7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
4.58
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article

Regulating the future of laboratory medicine: European regulatory landscape of AI-driven medical device software in laboratory medicine

Neda Milinković, Francisco A. Bernabéu-Andréu, Marc Thelen, Solveig Linko et al.
7 citations
Clinical Chemistry and Laboratory Medicine (CCLM)
Artificial Intelligence in Healthcare and Education
4.58
article

Regulating the future of laboratory medicine: European regulatory landscape of AI-driven medical device software in laboratory medicine

Neda Milinković, Francisco A. Bernabéu-Andréu, Marc Thelen, Solveig Linko, Guilaine Boursier, Pika Meško Brguljan, Hikmet Can Çubukçu, Duilio Brugnoni, Katerina Tosheska Trajkovska, Andrea Padoan
article en
7 citations

Abstract

Artificial intelligence (AI) is rapidly transforming laboratory medicine, impacting medical devices and healthcare practices. Despite these advancements, AI-based medical device software (MDSW) introduces a new layer of complexity in regulatory compliance. This paper outlines the regulatory landscape for MDSW and AI-driven MDSW, clarifying the responsibilities of laboratory professionals and manufacturers under the <i>In Vitro</i> Diagnostic Regulation (IVDR), ISO 15189:2022, and the Artificial Intelligence Act. An analysis of 89 MDSWs approved under the IVDR, derived from the European Database on Medical Devices (EUDAMED) reveals a diverse landscape of applications, ranging from digital pathology and molecular diagnostics to laboratory automation and clinical decision support. While Germany currently dominates the EU market for these devices, and the majority of approved MDSW remain non-AI driven and classified as low-risk, the increasing presence of AI-powered Class C devices underscores the growing potential of software in complex diagnostic scenarios. However, realizing the full potential of AI in laboratory medicine requires careful navigation of the evolving regulatory landscape. Key challenges persist, including defining intended use, ensuring robust clinical evidence, mitigating data bias, and establishing rigorous post-market surveillance. Balancing regulatory oversight with innovation is critical to fostering the development of trustworthy AI systems without stifling progress. As regulatory frameworks continue to evolve, establishing clear validation methodologies and transparent compliance pathways will be essential to unlocking the full potential of AI in laboratory medicine while ensuring the highest standards of safety and clinical effectiveness.

Clinical Chemistry and Laboratory Medicine (CCLM)Vol. 63(10)
Ministry of Health (TR), University of Padua (IT), Radboud University Nijmegen (NL), Inserm (FR), Université de Montpellier (FR), Radboud University Medical Center (NL), University of Belgrade (RS), Directorate of Health (IS), Centre de Référence des Maladies Autoinflammatoires et des Amyloses (FR), Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia (IT), Hospital Universitario Puerta de Hierro Majadahonda (ES), University Clinic of Pulmonary and Allergic Diseases Golnik (SI), Streekziekenhuis Koningin Beatrix (NL), Ss. Cyril and Methodius University in Skopje (MK)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Artificial Intelligence in Healthcare and Education
4.58
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