What are medical device clinical trials?
Medical device clinical trials are studies designed to generate clinical evidence on the safety, performance, and clinical benefit of a medical device. They play a central role in supporting regulatory approval, market access, and ongoing post-market evaluation, particularly for devices where bench testing or preclinical data alone are not sufficient to demonstrate acceptable benefit–risk.
A defining feature of medical device trials is that they do not simply mirror the structure or objectives of drug trials. Devices range from simple, low-risk products to complex, software-enabled or implantable technologies, and this diversity shapes how evidence is generated. Clinical investigations must therefore be tailored to the nature of the device, its intended use, and the risks it presents, rather than following a single, standardised development pathway.
Before any study design decisions are made, it is essential to establish whether a product is regulated as a medical device and what claims the clinical evidence is expected to support. This initial scoping step sets the boundaries for the trial programme, informs discussions with regulators and ethics committees, and underpins all subsequent decisions on study design, endpoints, and oversight.
Regulatory expectations vary across regions, but common themes include appropriate evidence for the device’s risk profile, clear traceability, and sound data integrity controls.
Medical device clinical trials vs drug trials
Medical device clinical trials differ from drug trials in several fundamental ways, and these differences influence almost every aspect of study design and execution. Treating device trials as a direct extension of pharmaceutical development can therefore lead to inappropriate designs, inefficient evidence generation, and avoidable regulatory questions.
Importantly, device classification is not just a regulatory label applied at submission. It shapes the entire clinical development strategy, from the choice of study objectives and endpoints through to the scale of the trial and the extent of post-market evidence required. Aligning the clinical trial approach with the device’s risk profile helps ensure that evidence generation is proportionate, credible, and fit for purpose. Key differences include:
Study pathway and terminology
Medical device trials typically follow stages rather than the fixed phase structure used in drug trials.
Iterative product development and data needs
One key distinction is the iterative nature of devices. Unlike drugs, which are typically fixed in composition once clinical testing begins, devices may undergo design refinements as usability issues, performance limitations, or manufacturing considerations are identified. Clinical evidence generation must therefore accommodate controlled change while maintaining traceability between device versions and the data collected. This also means device trials often generate data that feeds back into product improvement over time, including insights gathered after approval.
Endpoints and what ‘success’ looks like
Endpoints in medical device trials also extend beyond traditional measures of efficacy and safety. While adverse events and clinical outcomes remain important, studies often need to demonstrate technical performance, functional improvement, or usability in real-world settings. These endpoints are closely linked to the device’s intended use and are central to supporting labelling and claims.
Placebos, blinding, and control groups
Blinding and the use of a placebo can present practical and ethical challenges in device studies, particularly for surgical or interventional products. As a result, device trials frequently rely on alternative approaches to minimise bias, such as objective outcome measures, active comparators, or independent endpoint adjudication, rather than classic double-blind designs.
Patient population, sample size, and follow-up
Sample sizes in device trials are often smaller than in drug trials, reflecting narrower indications, specialist patient populations, or early market entry strategies. Follow-up requirements may also differ, with some devices requiring extended observation to understand durability, long-term safety, or performance over time.
Post-market evidence and lifecycle learning
Finally, evidence generation for medical devices does not end at approval. Post-market surveillance and post-market clinical follow-up are integral parts of the lifecycle, with real-world data feeding back into safety monitoring, performance assessment, and, in some cases, further product development. This lifecycle approach reinforces the need for trial designs and data systems that can support both pre-market and post-market evidence requirements.
Device classification and risk categories in medical device trials
Medical devices are regulated using a risk-based approach, and understanding how a device is classified is a critical early step in planning clinical evidence generation. Classification reflects the potential risk posed to patients and users and directly influences the level of regulatory scrutiny and the type of clinical data expected.
Class I (lower risk)
In general, lower-risk devices may require more limited clinical investigation, supported by existing evidence, performance testing, or literature.
Class II (moderate risk)
Risk classification also affects how a study is reviewed and overseen. Higher-risk devices typically trigger more extensive regulatory and ethics review, tighter controls on device use and accountability, and more formalised monitoring arrangements. These considerations need to be reflected in the study design, operational planning, and documentation from the outset.
Class III (higher risk)
Higher-risk devices are more likely to require robust, prospectively collected clinical data. The higher the potential risk, the greater the emphasis on demonstrating that the device performs as intended and that any residual risks are acceptable when weighed against the expected benefits.
Medical device clinical trial phases
Medical device clinical trials are commonly organised into stages that reflect the maturity of the device and the questions being addressed, rather than the fixed, sequential phases used in drug development. These stages are designed to build evidence progressively, with each one supporting a different decision point in the device lifecycle.
Early-stage studies
Early-stage studies, often described as pilot, first-in-human, or early feasibility studies, focus on initial safety, basic performance, and usability. At this point, the aim is to confirm that the device can be used as intended in a clinical setting and to identify any issues that need to be addressed before broader evaluation. These studies are typically small and tightly controlled, particularly for higher-risk devices.
Feasibility studies
These sit between early evaluation and confirmatory evidence generation. They are used to refine the clinical approach, assess preliminary effectiveness, and finalise key design elements such as endpoints, procedures, and patient selection. For many devices, feasibility work provides the evidence base needed to justify a larger, more definitive study.
Pivotal studies
These are designed to generate the primary clinical evidence required to support regulatory approval or market access. These trials focus on demonstrating that the device meets its intended performance and safety objectives in the target population. Study designs are more formalised, with greater emphasis on statistical robustness, predefined endpoints, and data quality.
Post-market stages
Post-market stages extend evidence generation beyond approval. Post-market clinical follow-up and surveillance activities are used to monitor long-term safety, durability, and performance in routine clinical use. This ongoing evidence supports risk management, informs updates to labelling or instructions for use, and may contribute to future device iterations or expanded indications.
Challenges medical device clinical trials face
Medical device clinical trials present a distinct set of challenges that span the full study lifecycle, from start-up through to close-out and commercial use. These challenges are closely linked to the nature of devices themselves and can materially influence timelines, costs, and evidence quality if not anticipated early.
Patient enrolment and study participation
Recruitment is often more complex in device trials than in drug studies. Eligibility may depend on anatomical, procedural, or disease-specific factors, and participation can require invasive procedures or specialist clinical settings. As a result, enrolment frequently relies on careful site selection, close investigator engagement, and additional patient support to ensure informed participation and retention.
Demonstrating economic and clinical value
Beyond safety and performance, many device programmes must also generate evidence that supports economic value. This may include demonstrating efficiency gains, reduced procedure times, or downstream cost savings for healthcare systems. Incorporating such considerations into clinical study design can strengthen the overall evidence package but adds complexity to endpoint selection and data collection.
Investigator responsibilities and device control
In medical device clinical trials, investigator responsibilities extend beyond participant care and protocol adherence to include strict control and accountability of the investigational device. These operational requirements are central to participant safety and to the credibility of the evidence generated.
Investigators are expected to use the device only as specified in the approved protocol and associated study documents. This includes following defined procedures for implantation, operation, or use, as well as any restrictions on who may use the device and under what conditions. Deviations can introduce safety risks and make trial results difficult to interpret.
Device control and accountability are also essential. Sites must be able to track what devices were received, where they were stored, who had access, which participant received which device (including relevant identifiers where applicable), and what happened to unused or returned devices. Maintaining accurate logs supports traceability, helps detect errors or misuse, and provides evidence of compliant handling during audits or inspections.
These responsibilities often require clear site processes, training, and documentation that are tailored to the device and study context. When managed well, device control reduces operational risk, supports regulatory confidence, and helps ensure that trial findings reflect the performance of the device under controlled and well understood conditions.
Conclusion
Medical device clinical trials are most effective when they are planned around the device itself: what it is, the risk it presents, and the claims the evidence must support. A clear view of classification, lifecycle stage, regulatory expectations, and site-level device control helps teams generate credible evidence without forcing a drug-trial template onto a fundamentally different development model.
At Quanticate we are experienced in medical device studies and in our 30 years history we have successfully partnered with many medical device companies to get their devices approved. If you are interested in how our medical device CRO expertise can be applied to your trial, please request a consultation below.
