It’s estimated that there are 3-4 million smart infusion pumps now deployed across the medical world. They are among the most successful new product introductions of recent years and at first glance appear to display all the characteristics we associate with traditional medtech devices: self-contained hardware units designed for performance and reliability in the execution of a well-defined role, in this case supporting decades-old infusion workflows.
But in the case of smart infusion pumps, appearances are deceiving. While they deliver clear safety and standardization benefits, those benefits depend on sustained governance, integration, and clinical alignment rather than the device alone. In effect, while they may look like traditional self-contained medtech devices (think portable surgical suction pumps or automated external defibrillators), that’s not the case.
Understanding how infusion pumps are different makes it possible to understand the widening gap between new product planning and new product execution. And why that gap is becoming more structural and permanent.
Intravenous treatments were once delivered via purely mechanical, gravity-based systems, essentially a bag on a pole with tubing, a drip chamber and a manual flow regulator. Maintaining a continuous, accurate stream of medication required constant attention from nurses and other clinicians. When infusion pumps came along in the 1960s (first with electromechanical switches and then microprocessors) nurses could set up the system, punch in a few numbers and the pump would take care of the rest, operating unattended. This was medtech at its best: a simple, reliable, standalone device that solved a real problem and could be widely deployed.
Making infusion pumps “smart” seems like a natural evolution of all of that, but really, it’s a very different device.
Equipped with drug libraries and dose-error reduction software, smart pumps don’t simply carry out clinical instructions, they actively evaluate them against predefined safety boundaries before and during infusion. But this means the units are no longer self-contained. Because these drug libraries and dosing limits are created and maintained outside the device, critical behavior is governed by systems beyond the manufacturer’s control.
Using smart pumps in diverse settings also poses challenges. A smart pump optimized for use in the ICU or on inpatient wards can lead to excessive overrides, inappropriate alerts, or unsafe configurations when used in the operating O.R. for home care.
And unlike earlier devices, today’s smart pumps sit on the network and are expected to work with other clinical systems. That means developers must plan for interactions among pharmacy systems, hospital IT infrastructure, clinical workflows and regulatory controls, many of which they do not control.
All of this changes the parameters for how developers evaluate risk and responsibility. Development plans that could once assume a device operating within a stable, knowable system boundary, must now flex to accommodate constantly changing software, networks, workflows, regulations, and threat environments. Safety, security, performance, human factors and compliance must also be addressed upfront, yet without a clear system boundary dependencies evolve continuously and require a breadth of expertise no single team can fully possess at any one moment.
This challenge has been building for years but was dramatically accelerated by the digitization of medical environments during and after COVID. Industry studies show that annual FDA clearances for SaMDs (Software as a Medical Device) that once numbered in the single digits took a sharp upward trend starting in 2016, with clearances nearly doubling year-over-year in 2020 and again in 2023.
Infusion pumps, while a major success story, have clearly had their share of problems. From 2005 through 2009, the FDA fielded some 56,000 reports of adverse events associated with the use of infusion pumps, including numerous injuries and deaths. During this time period, manufacturers conducted 87 infusion pump recalls.
To bridge the ever-widening planning-execution gap. organizations must shift from linear project plans to adaptive operating models. New product execution becomes a process of discovery and adaptation, not simple verification of a predefined plan.
In our work with device developers at Suntra, here’s what we are seeing:
Modular architectures: Developers today are shifting tosystem architectures that are more modular than ever, allowing software, cybersecurity controls and interoperability components to be updated without destabilizing core safety functions.
Ongoing risk management: Analysis of post-market hazards, such as software updates, vulnerability remediation, and workflow drift, are now included as part of ongoing risk management, not just limited to initial deployment. Similarly, human-factors analysis is now extended well beyond launch to address how users adapt and create workarounds over time.
Cross functional governance: Hardware engineering, software, security, human factors, quality, regulatory…it was once possible for these groups to function independently. Not anymore. We see them being increasingly integrated into cross-functional governance structures with a formal, standing decision body that operates from concept through post-market. This makes it possible for architecture assumptions, risk controls and safety claims to be explicitly owned and revisited as conditions change.
Execution ready: Take advantage of predefined impact-assessment pathways for change control to quickly evaluate software updates, security patches, and interoperability changes. This enhances the ability to execute necessary changes more quickly without destabilizing compliance. Use these pathways to ensure post-market surveillance data, including complaints and cybersecurity signals, feeds directly back into planning and validation activities.
What we are talking about here is a lifecycle-based model organized around the device as a living system rather than a one-time product. This aligns with modern expectations from regulators who increasingly expect manufacturers to manage software change, cybersecurity risk and real-world performance throughout the device lifecycle. A standing, cross-functional governance structure enables timely impact assessments, controlled updates and rapid response to post-market signals, directly supporting FDA guidance.
Addressing the planning–execution gap with a lifecycle-based model has become essential for providing regulators with the confidence that safety and performance claims will remain valid as devices, environments, and threats evolve.
At Suntra, we address this with our clients by collapsing strategy, design, and delivery into a single operating model.
Through consulting in the initial design phase, we enable clients to align regulatory, clinical, and commercial intent early. Establishing what’s achievable, as well as a proven process for getting there, is key to reducing the optimism bias that undoes so many efforts, as well as the late-stage rework that kills profitability. Engineering then embeds those decisions into execution-ready architectures, quality systems, and software pipelines that can evolve post-market.
Suntra augments internal teams with on-demand, cross-domain expertise, spanning systems engineering, human factors, software lifecycle, and regulatory strategy, recognizing that no organization can hold all required expertise at once.
Together, these capabilities turn execution from a reactive scramble into a managed, continuous process, allowing companies to deliver complex, software-driven medical devices with greater predictability, safety, and regulatory confidence.
Visit Suntra MedTech Solutions at https://SuntraMedTech.com/contact.