Medtech reality check #2
Why patient numbers alone do not tell you whether existing data will support the intended device, claims and regulatory strategy.
Clinical data can be valuable — but relevance matters
Clinical data can be one of the most valuable assets a medical-device company has.
But the existence of data does not, by itself, establish that the evidence is sufficient for the device, intended purpose and claims the company now plans to commercialize.
The key questions are what was studied, why it was studied, how the study was designed, which population was included, what endpoints were used and how closely the studied product corresponds to the product now being developed.
A large patient number may be reassuring, but it does not replace that assessment.
The study has to answer the right question
Before relying on existing clinical data, it is worth asking: What version of the product was studied? Was the intended purpose the same? Was the target population comparable? What clinical outcomes were measured? What claims could reasonably be supported by the results? Was the study appropriately designed and conducted for the question being asked?
The answers do not have to be identical in every case for data to remain useful. The regulatory assessment is device- and context-specific. But differences need to be understood and justified rather than assumed away.
This is why “we have data” and “we have sufficient clinical evidence” are different statements.
Timing matters
Clinical studies are expensive, and there is understandable pressure to start them early.
A study is visible progress. Sites open. Patients are enrolled. Milestones are achieved.
But starting clinical work before key product decisions are sufficiently mature can create a risk that the evidence no longer aligns well with the eventual commercial device.
That risk deserves particular attention for software and AI-enabled devices, where algorithms, model architecture, inputs, outputs, performance characteristics or intended clinical use may still be evolving.
This does not mean a product must be “finished” before every clinical activity begins. Development and evidence generation can be iterative. It does mean the company should understand what is stable, what may still change, and how those changes could affect the relevance of the evidence being generated.
The cost is not only regulatory
If the resulting evidence does not adequately support the final device or claims, the consequences may include additional studies, repeated validation work, changed claims, revised development plans or delayed submissions.
Those outcomes affect time and burn rate as much as they affect the regulatory file.
This is why clinical strategy should be connected to product and regulatory strategy before major clinical investments are made.
Moving quickly can be valuable. Moving quickly without enough clarity about what the study needs to prove can be very expensive.
A better question to ask
Instead of asking only “How much clinical data do we already have?”, ask: “What regulatory and clinical question does this data actually answer for the device we intend to commercialize?”
That shift sounds small, but it changes the conversation.
Existing data may turn out to be highly valuable. It may support part of the evidence package. It may reveal a gap that can be addressed efficiently. Or it may show that the clinical strategy needs to change.
Any of those answers is useful if you get it early enough.
About this series
MedTech Reality Checks is a practical LinkedIn series by Nadira Salah, CEO & Founder of MedQR Consulting, drawing on 10 years of experience in medical-device QA/RA and work with startups and smaller MedTech companies. The series focuses on recurring decision points where product, clinical, regulatory and business strategy meet.