Under the EU MDR, few manufacturers have the portfolio of large, randomized, long‑term studies across all indications and target populations. Therefore, it is necessary to use imperfect data to tell an honest and convincing story in the clinical evaluation. It is not a weakness. It is exactly what MDR expects when you pursue CE marking for medical devices.
Manufacturers more often have:
- A pivotal study with design limitations.
- Smaller, single‑center or retrospective data.
- Strong technical and bench evidence, but modest clinical numbers.
- Real‑world PMS and complaints data that are informative, but not always clean.
The question is not “Is the data perfect?” but “Can it be presented in a way that is transparent, clinically meaningful, and proportionate to the device risk?” That is the core of a defensible clinical evaluation under MDR.
Notified bodies know clinical data will have gaps. What they look for is:
- A clear link between intended purpose, clinical claims, and the evidence presented.
- Honest acknowledgement of uncertainties, biases, and limitations.
- A benefit-risk conclusion that is consistent with the totality of evidence and with the device’s risk class and intended use.
- A credible plan for how remaining uncertainties will be managed and reduced over time (PMS, PMCF, registries, publications).
You do not need to hide imperfections; you need to guide the reviewers on how to interpret them.
Here is how manufacturers can use imperfect data to support clinical evaluation of medical devices during CE marking.
1. Start with clear clinical claims
By narrowing the clinical claims, it will be easier to show that, even with limitations, the available data are appropriate for the device under evaluation.
2. Classify and make the limitations explicit
Categorize weaknesses and, for each limitation, explain how it could bias the results, how that bias was mitigated (supporting literature, other datasets, conservative interpretation) and what it means for the level of confidence in the claims.
3. Use triangulation instead of over‑relying on one study
With imperfect data, there is no single “hero” trial. Instead, triangulate core clinical studies for direct performance and safety, supportive literature and post-market data to cover longer‑term or broader populations.
4. Align claims to the strength of evidence
Many clinical evaluation challenges come from claims that are stronger than the data. With imperfect data, it is even more important to tighten the wording of intended purpose and clinical benefits so that each claim is genuinely supported. This reduces the gap between expectations and evidence, which is exactly where notified body questions appear.
5. Show active control of residual risk
Be explicit about residual uncertainties (e.g. limited data in certain age groups, comorbidities, or long‑term outcomes) and link them to specific PMS/PMCF activities.
Then the message becomes: “We know exactly where the gaps are, we monitor them, and we have a plan.” This is far more convincing than pretending the gaps do not exist.
Qserve can help you shape the best possible plan toward CE marking with the clinical data you currently have. Please reach out to us for any further information!
