TL;DR

• Treating all requirements the same leads to unnecessary testing and higher cost
• Categorizing requirements helps teams align verification rigor with risk and regulatory exposure
• A decision framework keeps verification defensible and efficient
• Progressive verification reduces surprises late in development and keeps schedules realistic
• Smart verification isn’t about doing less — it’s about proving what matters

The Verification Paradox in MedTech Development

In medical device development, verification is both a safeguard and a stress test, not just for the product, but for the process.

Most programs start with good intentions: test everything, demonstrate everything, document everything. But that ideal quickly collides with real-world constraints.

Every system must prove that it meets its intended requirements, but how teams decide what to verify and how deeply can make the difference between an efficient program and an expensive slog. Too much rigor, and you drown in testing that regulators never asked for. Too little, and you risk missing what matters.

At StarFish Medical, our teams are constantly navigating this balance. The sweet spot lies in proportional verification, applying the right level of scrutiny to each requirement based on its risk, impact, and audience.

Let’s unpack some strategies we’ve found helpful for right-sizing verification.

Using Requirements Categories to Right-Size Verification Effort

One of the most effective ways to achieve proportional verification is to categorize requirements according to their purpose and impact.

Here’s a structure that we like:

Category	Purpose	Verification Strategy
User / Clinical Needs	Define what the device must do for the clinician or patient.	Formal verification with documented evidence and traceability to clinical performance and use specifications (e.g., intended use, use environment, user populations)
Risk / Safety Requirements	Protect users and patients from harm.	Formal verification with documented evidence, worst-case testing, and traceability to risk controls.
Standards / Regulatory Requirements	Comply with applicable industry standards and regulations.	Formal verification with compliance test report and certification (as applicable), leveraging 3rd party testing services to reduce internal efforts.
Business / Market Requirements	Impose cost targets and brand or market features, clarify non-operational lifecycle (e.g., servicing)	Lighter verification — reviews, demonstrations, or simple analyses; sufficient to confirm design intent is met.
Internal / Technical Requirements	Guide subsystem design and integration.	Verified within engineering discipline; may not require regulatory-level rigor.

Categorization isn’t just about filtering requirements. It’s about filtering effort, giving each class of requirement the right balance of verification intensity and documentation.

We find that this approach helps clients optimize both cost and time. By explicitly tagging requirements that regulators care about (e.g., safety and effectiveness), we can avoid wasting energy formally testing business-driven features that won’t affect a regulatory submission.

The result? Cleaner documentation, faster submissions, and fewer questions from reviewers.

Building a Decision Framework for Proportional Verification

Even with categories in place, it can be helpful to look at things through a set of decision lenses to calibrate rigor dynamically:

• Risk and impact — If failure could harm a patient or compromise essential performance, it gets full verification, no debate.
• Complexity and coupling — The more interfaces or dependencies a requirement touches, the more you should consider verifying in detail.
• Change volatility — If requirements are still evolving or unstable, start with informal verification (e.g., reviews, spec checks), and formalize methods as they stabilize.
• Downstream cost — If a late failure would be expensive or irreversible (e.g., tooling, embedded code), check it early and thoroughly.
• Regulatory visibility — If it will appear in a submission or audit trail, it deserves formal documentation.

Additionally, in cases where requirements are tightly coupled or risk is mitigated collectively, it can be more efficient to verify at a higher system level rather than testing each component individually. This approach works best when:

• Lower-level requirements are not safety-critical on their own.
• Interfaces and interactions are well understood.
• System-level tests can demonstrate compliance without introducing gaps in traceability.

This framework keeps verification focused, defendable, and transparent — a balance that regulators appreciate and teams can sustain.

Adaptive Verification Strategies in MedTech Programs

Verification shouldn’t be a one-time event. As programs mature, the level of rigor should evolve with the risk landscape.

• Early phases: Focus on exploration and learning. Use simulations, quick tests, and informal reviews to validate assumptions.
• Development and design freeze: Increase formality. Convert informal checks into traceable verification protocols for safety-critical functions and validate test methods and measurement systems.
• Transfer and validation: Execute the formal tests that demonstrate compliance and essential performance.

This scalable verification model ensures that teams don’t spend months over-testing prototypes — but also don’t scramble to catch up before submission. It’s systems thinking applied to verification planning: treat the verification process as a living system that adapts as knowledge grows.

Why Proportional Verification Matters to MedTech Leaders

For executives and innovators, the message is clear: smart verification isn’t about cutting corners, it’s about cutting waste.

When verification strategy is tied to requirement categorization and guided by structured decision lenses, teams achieve three key outcomes:

• Efficiency — Less redundant testing, shorter development cycles.
• Clarity — Everyone knows what must be proven and why.
• Confidence — Regulators see a focused, defensible rationale instead of a data dump.

The MedTech companies that master this balance gain a competitive edge: they move faster, spend smarter, and still meet the highest standards of safety and effectiveness.

At StarFish, we aim to build this balance into our teams and programs, designing processes that serve both compliance and innovation.

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