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ManagementMedical Management A risk file should not be where design decisions go to be documented after the fact. It should help the team make those decisions in the first place. By Lavanya Ramnath Image credit: andresr / Getty Images (Creative #1938555104) October 29, 2026 Need to Know Risk management should influence medical device design decisions early, before architecture and verification plans are finalized.
Six decisions that shape FDA readiness for software as a medical device and connected digital health products A software team can build a compelling product and still reach the submission stage with a fundamental problem: the evidence supports a narrower claim than the business intends to make. The algorithm performs well, but the intended population has expanded. The clinical study answers one question, while the labeling promises something else.
Consider a hypothetical scenario that reflects a pattern increasingly reported by manufacturers: a 510(k) submission for an AI-powered diagnostic tool with 99% sensitivity. Strong numbers. Solid validation. And yet — a deficiency letter comes back from FDA. Not because the model underperforms. Because reviewers cannot determine what it is actually doing or why. This is the reality manufacturers are running into as AI/ML-based Software as a Medical Device (SaMD) enters the 510(k) and De Novo pathways.
Pediatric wearables are often treated as a niche extension of adult digital health, but that framing misses the real challenge. The hardest part is not miniaturizing the technology for smaller bodies. It is designing for a patient population that is constantly changing (physically, cognitively, behaviorally, and clinically) from infancy through adolescence.
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