AIQNET: A Simplified Route to MDR Approval

The rapidly changing regulatory landscape in the EU demands compelling technological solutions. AIQNET, initiated by RAYLYTIC, is aimed at producing a digital ecosystem that simplifies regulatory approval procedures by providing medical device manufacturers with access to ethically and legally collected, highly structured clinical data.

Funded by the German Federal Ministry of Economics and Technology and now with over 50 partner institutions, AIQNET is a digital platform that uses artificial intelligence (AI) to structure clinical data and automate MDR-related administrative procedures. AIQNET closes the gap between routine clinical and hospital care data and MDR pre- and post-market evaluation apparatuses.

AIQNET has already found applications in diverse branches of medicine. Most notably, AIQNET has increased the available evidence for complex surgical procedures on the spine and made these data available to medical device manufacturers.

Networking stakeholders

The power of AIQNET lies in its ability to connect stakeholders. On the one hand, medical technology and pharmaceutical manufactures can benefit from AIQNET’s advanced degree of interoperability between existing and emerging IT-systems, allowing them to rapidly collect, structure, and process routine care data to meet the demands of the MDR. Clinicians, on the other hand, can gain valuable clinical data through AIQNET that can serve to improve diagnostics, treatments plans.

In the AIQNET digital ecosystem, industry and patient care coexist, so that patients, manufacturers, and clinicians experience better outcomes.

New Medical Device Regulation in force since 2021

The Medical Device Regulation (EU) 2017/745 entails major changes for manufacturers, distributors, authorized representatives, and importers of medical devices in the European Union. Requiring more rigorous clinical evidence for certain classes of medical devices, the legislation foresees a drastic increase in both the quality and quantity of clinical data required to gain—and maintain—regulatory approval.

AIQNET, a cross-platform digital ecosystem, serves as a solution to the increasing pressure on medical and pharmaceutical manufacturers to collect, process, and transmit significant amounts of structured clinical data.

What is the MDR?

First published in 2017 and effective as of May 2021, the Medical Device Regulation (MDR) is a legal framework that introduces more stringency for developing and marketing medical devices. By means of new pre- and post-marketing evaluation procedures, it places additional demands on medical technology manufacturers to demonstrate the transparency, safety, and efficacy of their products throughout their lifetimes.

The MDR represents an update to a longer lineage of regulatory legislation affecting the medical technology industry in the European Union. It replaces the Medical Device Directive (93/42/EEC) (MDD) and the Active Implantable Medical Device Directive (90/385/EEC) (AIMD). In contrast to its directive predecessors, the MDR shifts the responsibility of enforcement from EU member states to medical device manufacturers themselves. Furthermore, the Annex XVI of the MDR widens the regulatory scope of the MDD and AIMD by extending pre- and post-market evaluation measures to products without an intended medical purpose—including contact lenses, equipment for electrical brain stimulation, and liposuction equipment.

The MDR grants products originally approved under the MDD and AIMD a four-year transition period ending in May 2021 to demonstrate compliance with the MDR. In-Vitro Diagnostic Devices, however, remain within the domain of the In-Vitro Diagnostic Devices Regulation (IVDR) and its May 2022 transition deadline.

In addition to widening the roster of medical devices subject to regulation, the MDR includes more stringent pre- and post-market regulatory mechanisms than its predecessors. In pre-market stages, more rigorous, highly structured clinical data must be transmitted to so-called notified bodies—independent organizations in change of certifying medium- and high-risk medical devices. Once the notified bodies perform conformity assessment procedures and the product is allowed onto market, some classes of medical devices are subject to post-market surveillance measures that must also be backed with clinical data.

Consequences for the medical technology industry

Although the MDR’s approach aims to generate more favorable outcomes, medical technology providers and the pharmaceutical industry are nevertheless burdened with demonstrating the safety and efficacy of their product with large amounts of clinical data.

This administrative hurdle has the potential to decelerate the release of products into the marketplace. Moreover, fulfilling the “post-market clinical follow-up” stipulated by the MDR has the possibility of being a costly, time-intensive, and legally precarious task. Combine these hurdles with a general IT skill shortage, decentralized data acquisition procedures in clinics and hospitals, and suboptimal interoperability of digital systems in the healthcare sector, and the surge in demand for data triggered by the MDR presents the medical technology and pharmaceutical sector with a unique challenge: rapid and cost-effective access to and transmission of large amounts of clinical data throughout the lifetime of a product—all while upholding patient data protection laws.

Routine care data from clinics and hospitals represent a possible route the pre- and post-market demands set up by the MDR. Most of the data collected as part of routine clinical care is not suitable for statistical analysis, let alone transmission to regulatory entities.

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The abstract “Accurate Wear Determination in Clinical Radiographs after Total Knee Arthroplasty using 2D-3D Registration and Artificial Intelligence: An In Vivo Validation” submitted to this year’s German Congress of Orthopedic and Trauma Surgery (DKOU) was accepted and nominated for the Wilhelm Roux Award. The work presents an automated algorithm for the accurate and precise measurement of wear in total knee arthroplasty using clinical AP radiographs.

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