How to Plan Software Evidence Before Building a SaMD Product

Evidence is a product deliverable, not a post-build activity

Software as a Medical Device (SaMD) teams often treat regulatory evidence as something that begins near submission. In practice, the quality of your evidence is determined by decisions made in the first weeks of product definition — how requirements are written, how risk is traced, how test cases map to clinical claims, and how changes are controlled.

Investors, notified bodies, and hospital customers increasingly ask for evidence maturity early. A credible evidence plan signals that your team understands regulated software delivery — not just feature development.

Start with intended use and clinical claims

Every piece of evidence should trace back to a defined clinical or operational claim. Vague intended use produces vague tests and weak submission packages.

• Intended use statement is precise about condition, population, and clinical decision supported.
• Clinical benefits are stated in measurable terms where possible.
• Contraindications and limitations are documented.
• User needs are captured separately from system requirements.
• Regulatory pathway per target market is identified (FDA, EU MDR, UK, etc.).

Build the requirements and traceability backbone

Traceability is the spine of SaMD evidence. Without it, verification becomes a collection of tests that may not defend your claims.

• User needs → design inputs → software requirements → architecture → test cases matrix is planned.
• Requirement IDs and versioning rules are established.
• SOUP components are identified with version pinning strategy.
• Interface requirements include clinical systems and devices where applicable.
• Non-functional requirements cover performance, security, and availability.

Risk management integrated with development

ISO 14971-aligned risk management should run parallel to development, not after feature freeze.

• Hazard identification workshops include clinical, engineering, and quality perspectives.
• Risk controls are classified as inherent design, protective measures, or information for safety.
• Residual risk evaluation criteria are agreed upfront.
• Cybersecurity risks are included in the risk file where connected.
• Risk traceability links to requirements and verification tests.

Verification and validation strategy

Plan V&V before coding so test environments, clinical datasets, and independent review roles are resourced correctly.

• Verification levels defined: unit, integration, system, regression.
• Validation includes clinical evaluation or simulated clinical workflow testing as appropriate.
• Test data strategy covers synthetic, anonymised real, and edge-case datasets.
• Automated test coverage targets are set for safety-critical modules.
• Defect classification and resolution workflow are documented.

Documentation structure from day one

A lightweight but complete documentation set prevents scramble before audit or submission.

• Software development plan and software requirements specification templates are ready.
• Architecture description includes deployment, data flows, and security boundaries.
• Release records and change control procedure are defined.
• Clinical evaluation or literature review plan is initiated if required.
• Post-market surveillance and complaint handling hooks are planned.