A tailored course, built for your situation
Mastering ISO 42001 for Senior Medical Device Compliance Executives
Build defensible, source-backed compliance frameworks that hold under peer review
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Peers questioning your AI compliance approach?
The situation this course is for
Even seasoned teams face pushback when introducing AI governance in regulated environments. Without concrete examples and traceable rationale, sound decisions get derailed by second-guessing.
Who this is for
Senior QA/RA executive in medical devices with deep regulatory experience and cross-functional influence
Who this is not for
Entry-level compliance staff, non-regulated sector practitioners, or teams without active AI/ML integration plans
What you walk away with
- Articulate the 'why' behind every ISO 42001 control using real-world regulatory precedents
- Reference FDA and EU MDR alignment strategies used in Class III device submissions
- Deploy justification templates vetted by notified bodies in audit settings
- Lead internal AI governance reviews with confidence, backed by documented reasoning
- Respond to engineering or clinical teams with specific examples and citations, not just policy statements
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and AI Governance
Understand the structure, scope, and intent of ISO 42001 in medical device contexts. Explore how it integrates with existing QMS frameworks like ISO 13485 and EU MDR.
12 chapters in this module
- Overview of ISO 42001 structure
- AI governance vs traditional risk management
- Regulatory drivers behind the standard
- Mapping to medical device lifecycle
- Relationship to EU AI Act
- FDA's AI/ML guidance alignment
- Key clauses for device manufacturers
- Role of QA/RA in AI oversight
- Notified body expectations
- Common misconceptions clarified
- Case study: Diagnostic software update
- Implementation timeline options
Module 2. Clause 4 Context and Leadership
Define organizational context for AI systems with precision. Document leadership responsibilities in a way that satisfies both internal auditors and regulatory reviewers.
12 chapters in this module
- Defining AI system boundaries
- Stakeholder identification techniques
- Regulatory context mapping
- Leadership obligation documentation
- Resource allocation decisions
- Management review integration
- Linking to quality policy
- Risk appetite statements
- Board-level communication protocols
- Supply chain considerations
- Example: Surgical robot oversight
- Template: Leadership attestation
Module 3. Clause 5 Planning
Develop a planning framework that anticipates regulator questions. Use proven methods to prioritize risks and set measurable objectives.
12 chapters in this module
- Risk identification for AI models
- Hazard analysis integration
- Objective setting methodology
- Resource planning templates
- Timeline development
- Regulatory milestone mapping
- Change management integration
- Clinical evaluation linkage
- Post-market surveillance planning
- Example: Autonomous infusion pump
- Documenting risk treatment plans
- Template: AI project charter
Module 4. Clause 6 Support
Ensure competence, awareness, and communication protocols support robust AI governance. Build evidence that holds under audit scrutiny.
12 chapters in this module
- Training program design
- Role-specific competency matrices
- Awareness campaign development
- Internal communication plans
- Documentation control methods
- Knowledge retention strategies
- External communication protocols
- Vendor training requirements
- Multilingual documentation handling
- Example: Cloud-based diagnostics
- Template: Training needs assessment
- Template: Communication log
Module 5. Clause 7 Operation
Implement controls that are repeatable, verifiable, and defensible. Focus on practical deployment aligned with development workflows.
12 chapters in this module
- Development lifecycle integration
- Version control requirements
- Model validation protocols
- Change control procedures
- Cybersecurity integration
- Data quality assurance
- Bias testing frameworks
- Performance monitoring setup
- Fail-safe mechanisms
- Example: AI-powered image analysis
- Template: Model release checklist
- Template: Retraining trigger criteria
Module 6. Clause 8 Monitoring and Evaluation
Establish KPIs and monitoring practices that demonstrate ongoing compliance. Prepare for regulatory inquiries with confidence.
12 chapters in this module
- Performance metric selection
- Accuracy tracking methods
- Clinical impact assessment
- Adverse event detection
- User feedback integration
- Audit readiness preparation
- Regulator question anticipation
- Trend analysis techniques
- Reporting frequency decisions
- Example: Remote patient monitoring
- Template: Dashboard summary
- Template: Nonconformance log
Module 7. Clause 9 Performance Evaluation
Conduct internal audits and management reviews that generate actionable insights. Use findings to strengthen governance maturity.
12 chapters in this module
- Internal audit planning
- Checklist development
- Objective evidence collection
- Finding severity classification
- Management review inputs
- Corrective action linkage
- Trend reporting methods
- Regulatory inspection simulation
- External audit preparation
- Example: Software as a Medical Device
- Template: Audit report
- Template: Management review agenda
Module 8. Clause 10 Improvement
Turn feedback and data into continuous improvement. Build a learning culture around AI compliance.
12 chapters in this module
- Corrective action workflow
- Root cause analysis methods
- CAPA integration
- Feedback loop design
- Lessons learned documentation
- Process optimization techniques
- Regulatory change adaptation
- Example: Adaptive algorithm update
- Template: Improvement register
- Template: Post-market surveillance report
- Change control closure
- Knowledge base integration
Module 9. Integration with ISO 13485
Align AI-specific requirements with existing QMS frameworks. Ensure seamless documentation and process integration.
12 chapters in this module
- Mapping ISO 42001 to ISO 13485
- Design control integration
- Risk management linkage
- Verification and validation planning
- Post-market surveillance alignment
- Change control harmonization
- Supplier management coordination
- Example: AI-enabled Class II device
- Template: Gap analysis worksheet
- Template: Integrated audit checklist
- Document hierarchy strategies
- Training program unification
Module 10. EU MDR and FDA Alignment
Demonstrate compliance with both EU and US regulatory expectations. Use documented precedents to defend decisions.
12 chapters in this module
- EU MDR AI classification
- FDA SaMD guidance application
- Clinical evaluation integration
- Performance evaluation planning
- Post-market clinical follow-up
- Transparency requirements
- Labeling considerations
- Example: AI-based triage tool
- Template: Regulatory strategy memo
- Template: Jurisdictional comparison chart
- Notified body interaction
- FDA pre-sub meeting prep
Module 11. Vendor Management for AI Systems
Ensure third-party AI providers meet stringent regulatory standards. Document oversight in a defensible manner.
12 chapters in this module
- Vendor selection criteria
- Contractual requirements
- Oversight frequency decisions
- Audit rights negotiation
- Model transparency demands
- Change notification protocols
- Example: Cloud-based diagnostic API
- Template: Vendor assessment form
- Template: Service level agreement
- Data privacy considerations
- Cybersecurity expectations
- Exit strategy planning
Module 12. Implementation Playbook
Apply everything learned to build a customized, defensible ISO 42001 implementation plan for your organization.
12 chapters in this module
- Readiness assessment
- Roadmap development
- Stakeholder engagement plan
- Resource allocation model
- Pilot project selection
- Change management strategy
- Training rollout plan
- Documentation standards
- Audit scheduling
- Example: Enterprise rollout
- Template: Project plan
- Template: Executive briefing
How this maps to your situation
- Pre-audit preparation
- Cross-functional challenge response
- Regulatory submission support
- Leadership advisory role
Before vs. after
Before
Relying on general compliance principles when challenged on AI governance decisions
After
Responding with specific examples, cited precedents, and structured reasoning that stakeholders accept
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for flexible completion over 6-8 weeks
If nothing changes
Without documented, source-backed justification, even sound AI compliance decisions can be overridden by louder voices without regulatory experience.
How this compares to the alternatives
Unlike generic compliance webinars, this course provides medical device-specific examples, regulator-tested language, and implementation templates you can adapt immediately.
Frequently asked
Is this course relevant to non-AI medical software?
Yes, the principles apply to any algorithm-driven system in a regulated device context, including rule-based and adaptive software.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I share the templates with my team?
Yes, all templates are licensed for use within your organization.
$199 one-time. Approximately 3 hours per module, designed for flexible completion over 6-8 weeks.
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours