Companies developing or deploying AI systems now face increasing scrutiny around risk classification, transparency and lifecycle governance. An AI management system (AIMS) aligned with ISO/IEC 42001 provides a structured way to address these challenges while significantly improving efficiency, quality, and innovation outcomes — and ensuring AI system are effective, safe, compliant, and trustworthy.
MedTech leaders must find a balance between the slow, careful world of medicine and the fast-paced expectations of investors. Real success comes from choosing high-quality science over quick shortcuts, as being thorough is the only way to build lasting trust and reach the market.
Many challenges of designing and validating pediatric digital health devices are over-looked across developmental stages. Regulatory strategy, human factors, software architecture, and algorithm performance are critical consideration in dynamic patient populations.
A persistent tension exists between the drive for rapid technological advancement, the mandate for government oversight, and the paramount importance of patient safety. It is a foundation for the U.S. Food and Drug Administration’s (FDA) 510(k) premarket notification process, the primary pathway for new devices to enter the market.
What is driving the need for increased transparency across the MedTech organization relative to product innovation, development and commercialization?
Commercialization strategy in 2026 and beyond is more than a checklist. It requires a new mindset where cybersecurity is seen as a patient safety imperative, data is treated as a critical strategic asset, and product lifecycle is an intelligent process.
Rene Zoelfl, Global Industry Advisor for PTC’s MedTech practice, shares how intelligent product lifecycle at Fresenius Medical Care connects cross-discipline teams through a digital fabric built on a shared data foundation.
How is software-enablement — connected devices and artificial intelligence — reshaping how products are conceived, developed, and deployed in clinical practice? Fragmented operations in large MedTech organizations are not keeping pace with the complexity of products in their pipelines.
The Service+Tech model embeds AI into the workflow of regulatory experts rather than treating technology as a standalone tool; an approach allowing organizations to adopt AI immediately, with no risk and no R&D investment, while keeping full confidence in the accuracy and regulatory readiness of submissions.
Hospitals are adding more connected devices than ever before—from patient wearables to asset tracking systems. Yet this digital transformation is being bottlenecked by an antiquated power infrastructure dependent on single-use batteries that create waste, demand constant maintenance, and compromise device reliability.
