Medical devices have evolved to the point where they no longer operate as standalone products. As these products become more connected, materiovigilance, the process of monitoring and evaluating the safety and performance of medical devices after they reach the market, is becoming increasingly complex. Modern devices natively connect to software platforms, mobile applications, cloud infrastructure, remote monitoring systems and broader treatment pathways that extend far beyond the device itself.
This shift is particularly important for pharmaceutical and biotech organizations developing newer drug-device combination products, where device performance and greater digital engagement increasingly intersect. As organizations embrace digital transformation, device safety programs must navigate new risks that can emerge across interconnected systems rather than within a single product.
Traditional safety workflows assumed devices generated a relatively predictable stream of complaints and performance data. Today’s safety teams are tasked with matching pace with post-market surveillance and evaluating information from numerous sources while ensuring compliance with increasingly complex global requirements. To do this successfully, organizations must reevaluate how data is collected, analyzed and leveraged.
The Growing Challenge of Visibility
Medical device manufacturers now have access to unprecedented volumes of operational data. With nearly 30% of the world’s total data being generated by healthcare, a drought of data is not a challenge. This includes service records, customer support interactions, maintenance logs, software performance metrics, product complaints and field actions, all of which provide valuable insight into device performance. Each data point contributes a piece of the safety puzzle. However, many organizations still struggle to connect those pieces into a coherent view. Combination products may generate signals that span both drug and device domains. While a signal may initially present as a device complaint, user error or adherence issue, it can ultimately carry broader implications for therapy effectiveness and patient outcomes.
The abundance of data does not necessarily mean fewer challenges. Teams can easily silo or isolate information, making it harder to identify potential device issues. For example, a trend that appears insignificant within one department may reveal a larger pattern when viewed alongside information from quality, regulatory, manufacturing or customer support teams. Without contextual backdrops, device and safety teams risk missing opportunities to intervene before a problem escalates.
As more devices continue to incorporate some level of software-driven functionality, this visibility becomes even more critical. Teams must now manage potential complications regarding software updates, cybersecurity considerations, connectivity issues and user-interface changes. Traditional surveillance models were not designed to address the digital enhancements that now influence device performance. Safety teams must evaluate not only the physical device but also the broader ecosystem in which it operates. As device ecosystems become more interconnected, traditional compliance-focused safety models are proving insufficient.
Moving Beyond Compliance-Centered Operations
Safety teams and the programs they deployed had historically focused on meeting reporting obligations and inspection requirements. While compliance remains a critical standard, it’s no longer the best guarantee of effective risk management. More organizations are shifting their view and treating surveillance as a strategic capability that enables them to gain a stronger understanding of how products perform in real-world environments.
This approach is more effective than introducing technology solely to compensate for fragmented processes. Teams must be open and willing to collaborate based on a foundation of shared knowledge. Safety teams should operate alongside quality, engineering, clinical, regulatory and commercial teams. With clear processes for sharing information and coordinating responses across departments, product performance becomes significantly more valuable.
One of the most critical benefits of clear communication and open collaboration is accelerated decision-making. When organizations clearly define team roles and provide access to consistent information, investigations progress more efficiently and teams can implement corrective actions with greater confidence. Prioritizing this level of coordination is becoming increasingly important as product portfolios expand across markets and regulatory jurisdictions.
Building the Foundation for Smarter Safety Operations
As technology advances, organizations are increasingly exploring automation, advanced analytics and AI, which aligns with broader life sciences priorities around digital transformation and operational modernization. These technologies help teams manage growing workloads without compromising operational efficiency. While these technologies provide modernized solutions to today’s safety challenges, their success depends on the quality of information beneath them.
Before fully benefiting from advanced technologies such as AI, organizations must establish guardrails for how information is collected, categorized and maintained. Safety programs generate large volumes of data, but value is not found in volume; it is found in consistency. Implementing standardized processes leads to the collection of reliable data, which supports accurate analyses and informed decision-making.
Several bricks are required to build the foundational elements that can help organizations strengthen their readiness to adopt technology. Some of these include:
- Consistent data definitions across departments and systems.
- Standardized workflows for intake, review and investigation activities.
- Strong documentation practices that support traceability and audit readiness.
Investing time and resources into these fundamentals creates an environment where advanced tools can deliver measurable value. The result is a more resilient operating model that supports both efficiency and accountability. This approach is more well-rounded than introducing technology to compensate for fragmented processes; organizations can use technology to enhance already well-defined workflows.
The Future of Device Safety
The future of materiovigilance will depend on organizations’ ability to analyze data at both the macro and micro levels. Contextual information, expansive expertise and technology will all play a critical role in a broader unified strategy. Medical products are only increasing in sophistication, and safety programs must keep pace to support better outcomes across the product lifecycle. As pharmaceutical and device combination products become more common, organizations face a continuous stream of data in which therapies, connected technologies and digital oversight blend into a complex ecosystem. To keep pace with this shift, safety programs must be built to handle rising data complexity, maintain compliance and enable innovation.
From a manufacturing standpoint, safety data, when leveraged effectively, provides real-world performance information that can guide product improvements, strengthen customer trust and enhance business decisions. The organizations that embrace this perspective will gain a clearer understanding of both product performance and patient experience.
Editor’s Note:
As Director, Safety Operations, in Lifecycle Safety at IQVIA, Dr. Padmalakshmi Jnaneshwar leads safety operations, regulatory reporting and project management teams supporting medical device pharmacovigilance, drug safety for clinical trials and post-marketing products, plus vaccine safety programs. A service operations leader with a strong project delivery track record, Dr. Jnaneshwar has over 20 years of experience delivering programs spanning multiple therapeutic areas across safety services. She holds an MBBS degree from Rajiv Gandhi University of Health Sciences and a post-graduate diploma in clinical trials.