Digital diagnostics, especially those based on artificial intelligence (AI), offer enormous potential for faster, more accurate, and more personalized diagnoses. However, the path from concept to market-ready medical device is complex: manufacturers of in vitro diagnostic medical devices (IVDs) face significant regulatory challenges when seeking to place AI-based software solutions on the market under the In Vitro Diagnostic Medical Devices Regulation (EU) 2017/746 (IVDR). This article provides a hands-on overview of the regulatory requirements for digital diagnostics and shows how to avoid common pitfalls - so you can bring your digital solution to market successfully and in compliance with the law.
There is no doubt: artificial intelligence is opening up new dimensions in diagnostics. Algorithms can analyze vast volumes of data within seconds, detect patterns, and make predictions. In many cases, they outperform human analyses—both in terms of speed and the volume of data they can process and consider. AI systems also handle a high degree of complexity with ease.
In in vitro diagnostics, AI systems are primarily used for:
Examples of current devices include:
Please note: These examples are provided solely to illustrate current developments in the field of digital in vitro diagnostics. They do not represent any endorsement, recommendation, or validation by Metecon. Product, manufacturer, and application information is based on publicly available sources as of the publication date. Given the dynamic nature of regulatory and technological developments, this information may change at any time.
AI and machine learning methods also play an increasingly important role in quality assurance, for example, in detecting equipment deviations. AI algorithms can
In this way, AI becomes not only a driver of diagnostic innovation, but also of operational efficiency.
The regulatory evaluation of AI in IVD systems presents new challenges for companies. In the EU, such systems must meet the requirements of the IVDR in combination with the European AI Act (Regulation (EU) 2024/1689), if the system qualifies as high-risk AI - which applies to most of the examples mentioned earlier.
Key considerations include:
Post-market surveillance (PMS) also takes on increased importance, as both regulations demand it. In addition to monitoring one’s own and similar products on the market, it is especially critical to continuously assess the rapidly evolving state of the (AI) art and to determine how such changes affect the safety and performance of the medical device.
What you should consider as a manufacturer or provider of AI-powered IVDs:
Digital biomarkers in the IVD space are based on the computer-assisted acquisition, analysis, and interpretation of biological signals derived from laboratory parameters, molecular profiles, or highly sensitive assays. Using AI and machine learning, complex patterns from multiple data sources are translated into meaningful diagnostic or prognostic scores—often faster and more accurately than conventional methods. Their particular value lies in personalized medicine, where they support evidence-based decisions regarding diagnosis, therapy, and monitoring, while also helping to ease clinical workloads.
Here are some product examples:
Companion diagnostics (CDx) in the IVD field serve to precisely identify patients who are likely to respond to a specific therapy or who may be at increased risk of adverse effects—based on specific molecular or genetic biomarkers. They function through targeted analysis of biomarkers in blood, tissue, or other samples using validated IVD tests (see previous section), and the results have direct therapeutic relevance.
Companion diagnostics also benefit from AI: they help identify predictive signatures for treatment response from genetic data. AI platforms for analyzing tumor profiles are already in clinical use in oncology. The combination of AI and IVD is thus opening up new diagnostic and therapeutic frontiers.
Examples include:
The integration of AI into IVD is fundamentally transforming clinical workflows. Physicians no longer receive static, individual test results, but data-driven, often predictive decision support tools. This can improve diagnostic certainty, accelerate treatment decisions, and enhance patient safety. At the same time, using such systems requires new competencies—both technical and ethical.
Importantly, AI is not intended to replace medical decision-making but to support it meaningfully. Acceptance depends above all on transparent communication of the tools’ validity, clinical utility, and added value.
Many manufacturers of digital, AI-based IVDs—especially startups and research-driven organizations—struggle to bring their innovative products into regulatory alignment. Often, they lack established processes that meet IVDR requirements or do not yet have frameworks in place to address new standards for software, AI, and cybersecurity. Even established companies often need to update their existing development and quality management processes, particularly because many legacy products have not yet been approved under the IVDR.
To systematically identify and close these regulatory gaps, we recommend a targeted gap analysis of existing processes, based on key standards such as:
Only in this way can companies establish robust, auditable processes, forming the basis for successful market access under both the IVDR and the EU AI Act.
But no worries: no project is too complex. Metecon supports you through the process with in-depth expertise in software and AI-based medical devices and in vitro diagnostics. Whether it’s process development, documentation, or audit preparation – we guide you from your current regulatory status to successful market entry.