Fda Consultant Specialist

FDA Consultant Specialist

FDA regulatory consulting for medical device manufacturers covering submission pathways, Quality System Regulation (QSR), HIPAA compliance, and device cybersecurity requirements.

Table of Contents

• FDA Pathway Selection
• 510(k) Submission Process
• QSR Compliance
• HIPAA for Medical Devices
• Device Cybersecurity
• Resources

Clarify First

Before selecting a pathway or assessing compliance, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Device class and predicate — Class I/II/III and whether a predicate device exists (drives 510(k) vs De Novo vs PMA)
• Intended use / indications — what the device claims and its use environment (sets the substantial-equivalence argument and clinical-evidence needs)
• Software/AI nature — SaMD, adaptive AI needing a PCCP, or connected device (cybersecurity/SBOM) (changes the required documentation set)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the analysis.

FDA Pathway Selection

Determine the appropriate FDA regulatory pathway based on device classification and predicate availability.

Decision Framework

Predicate device exists?
├── YES → Substantially equivalent?
│   ├── YES → 510(k) Pathway
│   │   ├── No design changes → Abbreviated 510(k)
│   │   ├── Manufacturing only → Special 510(k)
│   │   └── Design/performance → Traditional 510(k)
│   └── NO → PMA or De Novo
└── NO → Novel device?
    ├── Low-to-moderate risk → De Novo
    └── High risk (Class III) → PMA

Pathway Comparison

Pre-Submission Strategy

1. Identify product code and classification
2. Search 510(k) database for predicates
3. Assess substantial equivalence feasibility
4. Prepare Q-Sub questions for FDA
5. Schedule Pre-Sub meeting if needed

Reference: See fda_submission_guide.md for pathway decision matrices and submission requirements.

510(k) Submission Process

Workflow

Phase 1: Planning
├── Step 1: Identify predicate device(s)
├── Step 2: Compare intended use and technology
├── Step 3: Determine testing requirements
└── Checkpoint: SE argument feasible?

Phase 2: Preparation
├── Step 4: Complete performance testing
├── Step 5: Prepare device description
├── Step 6: Document SE comparison
├── Step 7: Finalize labeling
└── Checkpoint: All required sections complete?

Phase 3: Submission
├── Step 8: Assemble submission package
├── Step 9: Submit via eSTAR
├── Step 10: Track acknowledgment
└── Checkpoint: Submission accepted?

Phase 4: Review
├── Step 11: Monitor review status
├── Step 12: Respond to AI requests
├── Step 13: Receive decision
└── Verification: SE letter received?

Required Sections (21 CFR 807.87)

Common RTA Issues

QSR Compliance

Quality System Regulation (21 CFR Part 820) requirements for medical device manufacturers.

Key Subsystems

Design Controls Workflow (820.30)

Step 1: Design Input
└── Capture user needs, intended use, regulatory requirements
    Verification: Inputs reviewed and approved?

Step 2: Design Output
└── Create specifications, drawings, software architecture
    Verification: Outputs traceable to inputs?

Step 3: Design Review
└── Conduct reviews at each phase milestone
    Verification: Review records with signatures?

Step 4: Design Verification
└── Perform testing against specifications
    Verification: All tests pass acceptance criteria?

Step 5: Design Validation
└── Confirm device meets user needs in actual use conditions
    Verification: Validation report approved?

Step 6: Design Transfer
└── Release to production with DMR complete
    Verification: Transfer checklist complete?

CAPA Process (820.100)

1. Identify: Document nonconformity or potential problem
2. Investigate: Perform root cause analysis (5 Whys, Fishbone)
3. Plan: Define corrective/preventive actions
4. Implement: Execute actions, update documentation
5. Verify: Confirm implementation complete
6. Effectiveness: Monitor for recurrence (30-90 days)
7. Close: Management approval and closure

Reference: See qsr_compliance_requirements.md for detailed QSR implementation guidance.

HIPAA for Medical Devices

HIPAA requirements for devices that create, store, transmit, or access Protected Health Information (PHI).

Applicability

Required Safeguards

Administrative (§164.308)
├── Security officer designation
├── Risk analysis and management
├── Workforce training
├── Incident response procedures
└── Business associate agreements

Physical (§164.310)
├── Facility access controls
├── Workstation security
└── Device disposal procedures

Technical (§164.312)
├── Access control (unique IDs, auto-logoff)
├── Audit controls (logging)
├── Integrity controls (checksums, hashes)
├── Authentication (MFA recommended)
└── Transmission security (TLS 1.2+)

Risk Assessment Steps

1. Inventory all systems handling ePHI
2. Document data flows (collection, storage, transmission)
3. Identify threats and vulnerabilities
4. Assess likelihood and impact
5. Determine risk levels
6. Implement controls
7. Document residual risk

Reference: See hipaa_compliance_framework.md for implementation checklists and BAA templates.

Device Cybersecurity

FDA cybersecurity requirements for connected medical devices.

Premarket Requirements

Device Tier Classification

Tier 1 (Higher Risk):

• Connects to network/internet
• Cybersecurity incident could cause patient harm

Tier 2 (Standard Risk):

• All other connected devices

Postmarket Obligations

1. Monitor NVD and ICS-CERT for vulnerabilities
2. Assess applicability to device components
3. Develop and test patches
4. Communicate with customers
5. Report to FDA per guidance

Coordinated Vulnerability Disclosure

Researcher Report
    ↓
Acknowledgment (48 hours)
    ↓
Initial Assessment (5 days)
    ↓
Fix Development
    ↓
Coordinated Public Disclosure

Reference: See device_cybersecurity_guidance.md for SBOM format examples and threat modeling templates.

Resources

scripts/

references/

Usage Examples

# Track FDA submission status
python scripts/fda_submission_tracker.py /path/to/project --type 510k

# Assess QSR compliance
python scripts/qsr_compliance_checker.py /path/to/project --section 820.30

# Run HIPAA risk assessment
python scripts/hipaa_risk_assessment.py /path/to/project --category technical

FDA QMSR — Quality Management System Regulation

Transition from QSR (21 CFR 820) to QMSR

The FDA finalized the Quality Management System Regulation (QMSR) in January 2024, replacing the legacy Quality System Regulation (QSR) with ISO 13485:2016 alignment. The rule became effective February 2, 2026.

Key differences under QMSR:

• ISO 13485:2016 is incorporated by reference as the primary QMS standard
• FDA retains certain device-specific requirements not covered by ISO 13485 (e.g., complaint handling per 21 CFR 820.198)
• Organizations already ISO 13485 certified have a significant head start
• No separate FDA registration for QMS — single system serves both ISO and FDA

QMSR Transition Checklist

• Gap analysis: ISO 13485:2016 vs. current QSR compliance
• Update Quality Manual to reference ISO 13485 clause structure
• Map existing SOPs to ISO 13485 clauses
• Address FDA-specific retained requirements (complaint handling, MDR reporting)
• Train staff on ISO 13485 terminology and structure
• Update supplier agreements to reference new regulatory framework
• Conduct internal audit against QMSR requirements
• Update design history files to ISO 13485 Clause 7.3 format

AI/ML-Based Software as Medical Device (SaMD)

FDA AI/ML SaMD Framework

AI/ML SaMD Submission Requirements

AI/ML SaMD Submission Package
├── Algorithm description and architecture
├── Training data characterization
│   ├── Data sources and collection methods
│   ├── Demographics and representativeness
│   ├── Data quality and labeling methodology
│   └── Training/validation/test split rationale
├── Performance evaluation
│   ├── Pre-specified performance goals
│   ├── Standalone performance metrics (sensitivity, specificity, AUC)
│   ├── Subgroup analysis (age, sex, race, site)
│   └── Real-world performance data (if available)
├── Reference standard justification
├── Predetermined Change Control Plan (if adaptive)
├── Human factors / user interface
├── Cybersecurity documentation
└── Software documentation per IEC 62304

Good Machine Learning Practice (GMLP) Principles

1. Multi-disciplinary expertise throughout product lifecycle
2. Good software engineering and security practices
3. Representative training and test datasets
4. Independent test datasets separate from training
5. Reference datasets based on best available methods
6. Model design tailored to available data and intended use
7. Focus on performance of human-AI team
8. Clinical study testing demonstrates real-world performance
9. Users provided clear, essential information
10. Deployed models monitored for performance with retraining managed

Predetermined Change Control Plan (PCCP) for AI/ML Devices

PCCP Structure

PCCP Change Categories

Enhanced Cybersecurity Requirements (PATCH Act)

The PATCH Act (effective March 2023, codified in FD&C Act §524B) requires:

Cybersecurity Documentation for Premarket Submissions

Cybersecurity Premarket Package
├── Security risk assessment
│   ├── Threat model (STRIDE or equivalent)
│   ├── Security risk analysis per AAMI TIR57
│   └── Attack surface analysis
├── Security architecture
│   ├── Security controls implementation
│   ├── Cryptographic architecture
│   └── Network architecture and trust boundaries
├── SBOM (Software Bill of Materials)
│   ├── All software components (commercial, open-source, custom)
│   ├── Version information
│   └── Known vulnerability status
├── Security testing
│   ├── Static analysis (SAST)
│   ├── Dynamic analysis (DAST)
│   ├── Penetration testing report
│   ├── Fuzz testing results
│   └── Vulnerability scanning results
├── Lifecycle security plan
│   ├── Patch management process
│   ├── End-of-life/end-of-support plan
│   └── Customer communication plan
└── Coordinated vulnerability disclosure policy

Cross-Reference: EU AI Act for AI Medical Devices

AI-enabled medical devices must comply with both FDA requirements and EU AI Act when marketed in both jurisdictions:

See also: ../mdr-745-specialist/SKILL.md for EU MDR classification of AI/ML medical devices and ../risk-management-specialist/SKILL.md for ISO 14971 risk management for AI devices.

Updated 510(k) Electronic Submission Requirements (eSTAR)

eSTAR Mandate

As of October 1, 2023, FDA requires all 510(k) submissions to use the eSTAR template format. Paper submissions are no longer accepted.

eSTAR Section Mapping

Cross-Framework: FDA ↔ MDR ↔ ISO 13485 Mapping

Cross-references: See ../quality-manager-qms-iso13485/SKILL.md for ISO 13485 implementation aligned with QMSR, and ../mdr-745-specialist/SKILL.md for EU MDR technical documentation requirements.

FDA Regulatory Updates & Cross-Framework Integration

FDA QMSR — Quality Management System Regulation

The FDA is aligning 21 CFR Part 820 with ISO 13485:2016 through the Quality Management System Regulation (QMSR), effective February 2, 2026:

• Key Change: QSR (21 CFR 820) replaced by ISO 13485 as the recognized quality system standard
• Impact: Manufacturers must comply with ISO 13485:2016 instead of QSR-specific requirements
• Design Controls: ISO 13485 Clause 7.3 replaces 820.30
• CAPA: ISO 13485 Clause 8.5 replaces 820.90/820.100
• Transition: FDA accepting both QSR and QMSR during transition period

AI/ML-Based Software as Medical Device (SaMD)

• Predetermined Change Control Plan (PCCP): Required for AI/ML devices that learn and adapt
• Good Machine Learning Practice (GMLP): FDA's 10 guiding principles for AI/ML in medical devices
• Transparency: Clear labeling of AI/ML-based functionality and limitations
• Real-World Performance: Post-market monitoring of AI model performance drift
• Cross-reference: See eu-ai-act-specialist for EU AI Act requirements for AI medical devices

Enhanced Cybersecurity Requirements (PATCH Act)

• Premarket Submissions: Cybersecurity documentation required for all connected devices
• Software Bill of Materials (SBOM): Mandatory for all premarket submissions
• Coordinated Vulnerability Disclosure: Required policy for all connected device manufacturers
• Postmarket Patches: Cybersecurity patches exempt from 510(k) requirements
• Cross-reference: See infrastructure-compliance-auditor for technical cybersecurity checks

Cross-Framework Mapping (FDA ↔ MDR ↔ ISO 13485)

Troubleshooting

Success Criteria

• 510(k) submission accepted on first attempt -- zero RTA deficiencies, with all eSTAR sections complete, user fee verified, predicate identified, and SE comparison addressing all technological characteristics
• QSR/QMSR compliance score above 85% -- as measured by qsr_compliance_checker.py, with all critical subsections (design controls, CAPA, document control) showing evidence of implementation
• HIPAA technical safeguards fully implemented -- AES-256 encryption at rest, TLS 1.2+ in transit, MFA enforced, audit controls active, and automatic logoff configured for all systems handling ePHI
• FDA submission timeline targets met -- 510(k) traditional within 90 days, De Novo within 150 days, PMA within 180 days, tracked via fda_submission_tracker.py milestones
• QMSR transition completed -- Quality Manual references ISO 13485 clause structure, all SOPs mapped, FDA-specific retained requirements addressed, and internal audit conducted against QMSR requirements
• Cybersecurity documentation complete for all connected devices -- SBOM, threat model, security testing reports, vulnerability disclosure policy, and patch management plan included in premarket submissions

Scope & Limitations

In Scope:

• FDA regulatory pathway selection (510(k), De Novo, PMA) with decision framework and comparison
• 510(k) submission process including eSTAR requirements, SE comparison, and RTA prevention
• Quality System Regulation (21 CFR 820) and QMSR (ISO 13485:2016 alignment) compliance assessment
• HIPAA Security Rule safeguard evaluation for medical device software
• Device cybersecurity requirements including SBOM, threat modeling, and PATCH Act compliance
• AI/ML SaMD framework including PCCP, GMLP principles, and training data characterization
• Cross-framework mapping between FDA, EU MDR, and ISO 13485

Out of Scope:

• Preparation or writing of actual FDA submission documents -- this skill provides frameworks and gap analysis, not document authoring
• Clinical trial design, execution, or statistical analysis for PMA clinical data
• FDA establishment registration, device listing, or UDI system implementation
• Post-market surveillance reporting (MDR, MedWatch) beyond process guidance
• De novo classification request scientific review preparation
• Direct interaction with FDA reviewers or Pre-Submission (Q-Sub) meeting facilitation

Important Notes:

• The QMSR became effective February 2, 2026 -- all manufacturers must now comply with ISO 13485:2016 as incorporated by reference, with FDA-specific retained requirements
• The Quality System Inspection Technique (QSIT) has been withdrawn and replaced with updated inspection procedures under Compliance Program 7382.850
• Risk-based thinking is now expected across all QMS processes under QMSR, not just design controls

Integration Points

Tool Reference

fda_submission_tracker.py

Tracks FDA submission milestones and calculates regulatory timelines for 510(k), De Novo, and PMA pathways.

Output: Milestone tracking with completion status, timeline calculations against FDA review goals, phase progress (planning, preparation, submission, review, decision), and overdue milestone alerts.

qsr_compliance_checker.py

Assesses compliance with 21 CFR Part 820 / QMSR by analyzing project documentation for evidence of implementation.

Output: Per-section compliance status, evidence found (document patterns and keyword matches), compliance percentage, gap identification with required evidence descriptions.

hipaa_risk_assessment.py

Evaluates HIPAA Security Rule safeguards for medical device software and connected devices.

Output: Per-safeguard compliance status across administrative (Section 164.308), physical (Section 164.310), and technical (Section 164.312) categories, with weighted scoring, evidence detection, and remediation recommendations.