How to score CAPA priority in a QMS
Triage device complaints with severity, occurrence, and detectability, then match the band to ISO 13485 CAPA actions without treating RPN as a requirement.
Clinical research notes, regulatory guidance, and engineering deep dives from the NexaMedTech team.
We publish practitioner notes from clinical engineers and regulatory scientists working on real diagnostics, biosensors, and connected care. Expect plain-language explainers, checklists you can use tomorrow, and deep dives that respect nuance.
Popular themes include ISO 14971 risk thinking, 10993 biological evaluation, SaMD evidence and model validation, manufacturability at small scale, and the unglamorous plumbing that keeps PHI safe.
We publish practical notes for teams building diagnostics, wearable biosensors, and AI‑health systems. Each article is written by clinical engineers who ship regulated software and devices, with enough detail that a reviewer can reproduce the claims. We focus on methods, data provenance, and the trade‑offs behind design choices rather than hype cycles.
Topics span study design and validation, interoperability, privacy and compliance, and manufacturability for connected care. When AI models appear, we discuss how to benchmark them against classical baselines and how to present results a clinical reviewer can audit. Our goal is a shared playbook the field can reuse.
If you want us to cover a specific question, or you are working through a tricky regulatory or engineering decision, contact our team. We are happy to help.
Triage device complaints with severity, occurrence, and detectability, then match the band to ISO 13485 CAPA actions without treating RPN as a requirement.
Compute Cohen's d and Hedges' g from two group means and SDs, or one-sample d, and read the conventional bands without treating them as a clinical rule.
Confirm a device or study payload is JSON with a FHIR resourceType, walk a Patient example, and know when you still need the official HL7 FHIR validator.
Unlock proactive compliance in medical device software development with predictive AI.
A first pass from class, predicates, and novelty. Confirm it on the FDA classification database and with counsel.
Use a simple 5 by 5 grid to compare hazards, then keep the real scales in the risk management plan.
A first pass for equal two-arm studies of means or proportions. Size the study on the effect that matters.
A low p value is not the finish line. Pair it with the size of the effect before making a claim.
A practical first pass for labeling, software, manufacturing and design changes, and when to open a regulatory impact review.
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Practical guide for MedTech DevOps/QA managers to implement CI/CD for medical device software.
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CTOs: Learn how AI-powered agentic systems are revolutionizing MedTech compliance in 2026.
Leverage Agentic AI for continuous GxP compliance monitoring. This guide covers frameworks for FDA 21 CFR 820, ISO 13485, HIPAA, IEC 62304.
Learn how Agentic AI reduces ISO 13485 audit preparation time for medical device software, boosting compliance and operational efficiency.
A CTO's guide to automating EU MDR compliance with agentic AI: frameworks, implementation challenges and benefits for MedTech regulatory teams.
How agentic systems cut QMS audit prep for device makers, mapped to FDA 21 CFR 820, ISO 13485 and IEC 62304 evidence requirements.
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Compressing turnaround time does not just speed up care — it changes the clinical decision itself. A look at three deployments and what the data showed.