Mika Reinikainen
Mika Reinikainen, LL.M., MBA, Managing Director, Abnovo Ltd
Mika Reinikainen set up his own medical device consulting company, Abnovo Ltd., after leaving Quintiles as Vice President in 2007. His practice focuses on regulatory strategy and compliance, as well as resolving manufacturers’ conflicts with Notified Bodies and Competent Authorities. He also provides regulatory interpretation and advocacy, particularly on borderline determination between legal regimes.
He has more than 40 years of experience in the European medical device field, including as regulatory affairs manager in industry (Pfizer Hospital Product Group of Companies), healthcare legal counsel (Hogan & Hartson), and regulatory consultant (Medical Technology Consultants Europe, BRI, and Quintiles).
He was directly involved in developing the Medical Devices Directives (as Consultant to the European Commission and through various roles in trade associations) and technical standards (former Chairman of CEN TC 257). He chaired the working group that developed the European medical device classification system. He was a member of the MDEG and MDCG expert groups on Borderlines and Classification, New Technologies, and Annex XVI.
He is a founder and past Chairman of the European Association of Authorised Representatives (EAAR) and former Vice President Europe of the Regulatory Affairs Professionals Society (RAPS).
He is currently the Chairman of the UK Responsible Person Association (UKRPA).
He holds a Master’s degree in law from the University of Nice (France) and a Master’s in Business Administration from Wharton (University of Pennsylvania, USA).
Topics
Utilization of AI in post-market surveillance
Artificial intelligence (AI) could transform post-market surveillance (PMS) of medical devices.
Under the EU Medical Device Regulation (MDR), manufacturers must establish comprehensive, continuous, proactive surveillance systems across the product lifecycle. AI technologies can augment the existing PMS system by automating literature reviews, monitoring adverse event databases, and analysing diverse real-world data sources such as clinical studies, complaints, and electronic health records.
Key applications include automated data collection, signal detection, trend analysis, and predictive risk assessment, which enhance the speed and accuracy of identifying safety issues. Potentially AI can also streamline regulatory compliance by generating Periodic Safety Update Reports (PSURs), post-market surveillance reports, and documentation updates through natural language generation.
Challenges remain: data quality, integration with existing systems, regulatory validation, and dual compliance with MDR and the EU AI Act. Nevertheless, AI adoption is accelerating, promising significant efficiency improvements, reduced manual burden, and enhanced patient safety through real-time, data-driven oversight.
The emergent landscape of novel AI technologies also provides an opportunity to reconceptualise the PMS system. The legal requirements of PMS could be met by developing an operational framework built from the ground up using AI native technologies.