AI and MedTech adoption and post-market governance
AI Toolkit
A practical internal toolkit I authored to turn AI/MedTech regulation, evidence, data governance and implementation considerations into usable advisory guidance.
- Plan
- Data
- Model
- Validate
- Monitor
Quick scan
- Role
- Author of an internal AI/MedTech toolkit for innovation advisory work.
- Timeframe
- Placement period, 2024-2025
- Context
- Health Innovation East internal governance and advisory support.
- Work mode
- Independently authored guidance-support material.
- Outputs
- Topic summaries, checklists and practical governance framing for advisory conversations.
- Why it matters
- Shows I can translate dense governance requirements into usable decision support.
Context
AI-enabled medical technologies create a translation problem: a product may be technically interesting, but adoption depends on regulation, evidence standards, clinical safety, information governance, interoperability and monitoring after deployment.
My role
I authored the toolkit during my Health Innovation East placement. It was practical internal guidance-support material for innovation advisory work, not formal regulatory advice, legal advice or a substitute for specialist clinical-safety review.
Approach
I drew on official publications from regulatory and health-system sources, alongside learning from the East of England AI Forum, and translated the material into usable guidance for advisory contexts.
- AI as a medical device and software as a medical device framing.
- MHRA and UKCA regulatory awareness.
- NICE evidence expectations and DTAC considerations.
- DCB0129 and DCB0160 clinical safety awareness.
- Information governance, data protection, interoperability, risk and post-market monitoring.
Selected outputs
- Structured guidance-support material.
- Topic summaries and practical explanatory sections.
- Governance-aware framing for innovator support.
- Checklists that helped turn broad AI/MedTech issues into more concrete questions.
What this shows
This work shows that I can turn a dense governance area into something other people can actually use. I translated regulation, evidence expectations, clinical safety, information governance, interoperability and post-market questions into practical guidance that made advisory conversations more structured and useful.