D.2.4: Validation Execution Evidence Package

Document ID: CODITECT-BIO-VAL-004 Version: 1.0.0 Effective Date: 2026-02-16 Classification: Internal - Restricted Owner: Validation Manager

Document Control

Approval History

Role	Name	Signature	Date
Validation Manager	[Pending]	[Digital Signature]	YYYY-MM-DD
QA Director	[Pending]	[Digital Signature]	YYYY-MM-DD
Quality Head	[Pending]	[Digital Signature]	YYYY-MM-DD
Regulatory Affairs Director	[Pending]	[Digital Signature]	YYYY-MM-DD

Revision History

Version	Date	Author	Changes	Approval Status
1.0.0	2026-02-16	Validation Team	Initial release	Draft

Distribution List

Executive Leadership Team
Quality Assurance Team
Validation Team
Information Security Team
Regulatory Affairs
Internal Audit

Review Schedule

Review Type	Frequency	Next Review Date	Responsible Party
Annual Review	12 months	2027-02-16	Validation Manager
Post-Audit Review	As needed	N/A	QA Director
Regulatory Update Review	As needed	N/A	Regulatory Affairs

1. Purpose and Scope

1.1 Purpose

This document establishes the framework for collecting, storing, organizing, and packaging validation evidence for the CODITECT Biosciences Quality Management System (BIO-QMS) platform to ensure:

Regulatory Compliance - Full conformance with FDA 21 CFR Part 11, EU Annex 11, HIPAA, and SOC 2 requirements
Evidence Integrity - Tamper-evident storage and cryptographic verification of all validation artifacts
Complete Traceability - Bidirectional linkage from requirements through design, testing, and evidence
Audit Readiness - 15-minute retrieval guarantee for any validation artifact during regulatory inspections
Deviation Management - Systematic capture, assessment, and resolution of validation deviations

1.2 Scope

This policy applies to:

In Scope:

All validation execution activities (IQ, OQ, PQ)
Evidence collection from automated test scripts
Manual test execution evidence (screenshots, observations)
Traceability matrix generation and maintenance
Deviation detection, classification, and tracking
Evidence package assembly for regulatory submission
Audit trail integrity for evidence chain of custody

Out of Scope:

Protocol development procedures (covered in D.2.1)
Electronic signature procedures (covered in D.2.3)
Validation review and approval workflows (covered in D.2.5)

1.3 Audience

Primary: Validation Engineers, QA Engineers, Test Engineers
Secondary: Quality Management, Regulatory Affairs, IT Operations
Reference: Auditors, FDA Inspectors, Executive Leadership

2. Evidence Collection Framework

2.1 Evidence Types

All validation evidence MUST be categorized into one of the following types:

Evidence Type	Description	Collection Method	Retention Period
Test Execution Logs	Automated test script output (JSON, XML, HTML)	Automated capture via test framework	7 years post-validation
Screenshots	UI state verification, error messages, approval workflows	Manual capture (PNG) with metadata	7 years post-validation
Configuration Captures	System configuration snapshots (JSON, YAML)	Automated export via API	7 years post-validation
Database Queries	SQL query results proving data integrity	Automated execution with result logging	7 years post-validation
API Response Captures	RESTful API request/response pairs (JSON)	Automated via test harness	7 years post-validation
Log File Excerpts	Application log segments showing specific behaviors	Automated extraction with timestamps	7 years post-validation
Audit Trail Reports	Immutable audit log exports for specific test cases	Automated export from audit service	10 years
Performance Metrics	Response times, throughput, resource utilization	Automated collection via monitoring tools	7 years post-validation
Security Scan Results	Vulnerability scan reports, penetration test findings	Automated via security scanning tools	7 years post-validation
Certificate/Key Evidence	PKI certificate chain verification, key rotation logs	Automated via HSM/KMS audit logs	7 years post-validation

2.2 Evidence Metadata Schema

Every evidence artifact MUST include the following metadata (stored in JSON sidecar file):

{
  "evidence_id": "EV-2026-02-16-00001234",
  "evidence_type": "screenshot",
  "test_case_id": "TC-IQ-001-SYSTEM-LOGIN",
  "protocol_id": "VP-BIO-QMS-IQ-001",
  "test_step": "4.2.1",
  "timestamp": "2026-02-16T14:32:18.123456Z",
  "collector": {
    "type": "manual",
    "user_id": "U-8472",
    "user_name": "Jane Doe",
    "authentication_method": "sso_reauth"
  },
  "environment": {
    "system_version": "1.0.0-rc1",
    "hostname": "bio-qms-validation-env-01.internal",
    "database_version": "PostgreSQL 15.3",
    "browser": "Chrome 120.0.6099.129",
    "os": "Ubuntu 22.04 LTS"
  },
  "integrity": {
    "sha256_hash": "a3c5f8d2e1b4c9a7f3e8d2b1a5c7f9e3d8b2a4c6f1e9d3b7a2c5f8e4d1b9a6c3",
    "signature": "ECDSA-SHA256:3045022100e5b2c8f9a3d7e1b4c6a8f2d9e3b5c7a1f8e2d4b6c9a3f5e7d1b8c2a4f6e9d3022034f7a2e9d1b6c8a3f5e2d7b9c4a1f8e6d3b2a5c9f7e4d1b3a8c6f2e5d9b7a4c1",
    "signing_key_id": "validation-evidence-signing-key-2026"
  },
  "chain_of_custody": [
    {
      "action": "collected",
      "timestamp": "2026-02-16T14:32:18.123456Z",
      "actor": "U-8472",
      "location": "validation-workspace-01"
    },
    {
      "action": "uploaded",
      "timestamp": "2026-02-16T14:32:25.789012Z",
      "actor": "evidence-collection-service",
      "location": "gs://coditect-bio-qms-validation-evidence/2026-02-16/"
    }
  ],
  "pass_fail": "pass",
  "expected_result": "Login successful with valid credentials",
  "actual_result": "Login successful, redirected to dashboard",
  "notes": "Screenshot captured immediately after successful authentication"
}

2.3 Automated Evidence Collection Scripts

2.3.1 Test Execution Evidence Script

Location: validation/scripts/collect-test-evidence.py

Functionality:

Executes test protocol steps from JSON specification
Captures stdout/stderr from test scripts
Screenshots browser state at each verification point
Queries database for data integrity checks
Captures API responses with request/response timing
Generates evidence metadata automatically
Computes SHA-256 hash of each artifact
Digitally signs evidence package with validation signing key

Example Usage:

python3 validation/scripts/collect-test-evidence.py \
  --protocol VP-BIO-QMS-IQ-001 \
  --test-case TC-IQ-001-SYSTEM-LOGIN \
  --environment validation \
  --collector-id U-8472

Output Structure:

evidence/
└── 2026-02-16/
    └── TC-IQ-001-SYSTEM-LOGIN/
        ├── execution-log.json
        ├── screenshot-step-4.2.1.png
        ├── screenshot-step-4.2.1.metadata.json
        ├── database-query-result-step-4.3.1.json
        ├── database-query-result-step-4.3.1.metadata.json
        ├── api-response-step-4.4.1.json
        ├── api-response-step-4.4.1.metadata.json
        └── evidence-manifest.json

2.3.2 Configuration Capture Script

Location: validation/scripts/capture-system-config.py

Functionality:

Exports Django settings (sanitized, no secrets)
Captures PostgreSQL configuration
Exports Nginx/load balancer configuration
Captures KMS key policy configurations
Exports IAM role/policy definitions
Captures network security group rules
Generates configuration baseline snapshot

Example Usage:

python3 validation/scripts/capture-system-config.py \
  --environment validation \
  --output evidence/2026-02-16/config-baseline/ \
  --sign

2.3.3 Audit Trail Evidence Extractor

Location: validation/scripts/extract-audit-evidence.py

Functionality:

Queries audit service for specific test case events
Exports audit log entries with integrity chain verification
Validates HMAC-SHA256 chain for tamper detection
Generates human-readable audit report (PDF)
Preserves original JSON for machine verification

Example Usage:

python3 validation/scripts/extract-audit-evidence.py \
  --test-case TC-OQ-005-APPROVAL-WORKFLOW \
  --start-time "2026-02-16T10:00:00Z" \
  --end-time "2026-02-16T11:00:00Z" \
  --output evidence/2026-02-16/TC-OQ-005-APPROVAL-WORKFLOW/audit-trail.json

2.4 Manual Evidence Collection Procedures

2.4.1 Screenshot Capture Procedure

Tools: Greenshot (Windows), Flameshot (Linux), Cmd+Shift+4 (macOS)

Procedure:

Pre-Capture Checklist:
- Verify correct test environment URL
- Ensure test data is loaded per protocol
- Clear browser cache if required by test step
- Position browser window to show full relevant content
Capture Screenshot:
- Capture full screen or relevant application area
- Include timestamp in system taskbar/menu bar
- File naming: {test-case-id}_step-{step-number}_{description}.png
- Example: TC-IQ-001_step-4.2.1_successful-login.png
Immediate Metadata Creation:
- Complete evidence metadata JSON template
- Include actual vs. expected result comparison
- Note any anomalies or observations
- Record pass/fail determination
Hash and Sign:
- Run sha256sum on PNG file
- Add hash to metadata JSON
- Sign metadata with validation key (automated via upload script)
Upload to Evidence Repository:
- Upload PNG + JSON to GCS bucket
- Verify upload success (receipt confirmation)
- Record upload in chain of custody log

2.4.2 Database Query Evidence Procedure

Tools: pgAdmin, psql CLI, DBeaver

Procedure:

Prepare Query:
- Copy query from test protocol specification
- Verify query targets correct database (validation environment)
- Review expected result criteria
Execute Query:
- Run query in read-only transaction (BEGIN; SET TRANSACTION READ ONLY;)
- Capture full result set (CSV or JSON export)
- Record execution timestamp and query duration
- Capture query plan if performance verification required
Result Documentation:
- Export results to JSON: {test-case-id}_db-query-step-{step}.json
- Create metadata JSON with query SQL, row count, pass/fail
- Compare actual result to expected criteria in protocol
- Document any discrepancies
Verification:
- Independent QA reviewer re-executes query
- Compare QA result hash to original evidence hash
- Both hashes must match for evidence acceptance

3. Evidence Storage Architecture

3.1 Tamper-Evident Storage Requirements

All validation evidence MUST be stored in a tamper-evident architecture that satisfies:

Append-Only: Evidence cannot be modified or deleted after initial write
Hash-Verified: Every artifact has SHA-256 hash stored separately
Integrity Chain: Evidence linked via cryptographic hash chain (Merkle tree)
Access Audit: All read operations logged with user identity and timestamp
Encryption at Rest: AES-256-GCM encryption for all stored artifacts
Geographic Redundancy: Multi-region replication with 99.999% durability

3.2 Cloud Storage Configuration

Primary Storage: Google Cloud Storage (GCS)

Bucket Configuration:

bucket_name: coditect-bio-qms-validation-evidence
location: US (multi-region)
storage_class: STANDARD (frequent access during validation, transition to NEARLINE after 90 days)
versioning: ENABLED (all overwrites create new version)
object_lifecycle:
  - action: SetStorageClass
    condition:
      age_days: 90
      matches_storage_class: STANDARD
    storage_class: NEARLINE
  - action: SetStorageClass
    condition:
      age_days: 365
      matches_storage_class: NEARLINE
    storage_class: COLDLINE
retention_policy:
  retention_period_days: 2555  # 7 years
  is_locked: true  # Prevents deletion even by bucket owner
encryption:
  default_kms_key: projects/coditect-bio-qms/locations/us/keyRings/validation/cryptoKeys/evidence-encryption-key
  algorithm: AES-256-GCM
access_control:
  uniform_bucket_level_access: true  # IAM-only, no legacy ACLs
iam_bindings:
  - role: roles/storage.objectViewer
    members:
      - serviceAccount:validation-evidence-reader@coditect-bio-qms.iam.gserviceaccount.com
      - group:qa-team@coditect.ai
  - role: roles/storage.objectCreator
    members:
      - serviceAccount:evidence-collection-service@coditect-bio-qms.iam.gserviceaccount.com
audit_logging:
  log_type: DATA_READ  # Log all object access
  log_type: DATA_WRITE # Log all object creation

Object Naming Convention:

{protocol-id}/{execution-date}/{test-case-id}/{evidence-type}/{artifact-name}

Examples:
VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-001-SYSTEM-LOGIN/screenshot/step-4.2.1-successful-login.png
VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-001-SYSTEM-LOGIN/screenshot/step-4.2.1-successful-login.metadata.json
VP-BIO-QMS-OQ-002/2026-02-17/TC-OQ-005-APPROVAL-WORKFLOW/audit-trail/approval-chain-complete.json

3.3 Integrity Chain Implementation

Merkle Tree Structure:

Each validation protocol execution generates a Merkle tree of all evidence artifacts:

                         Root Hash (signed with validation key)
                                /              \
                    Hash(E1 + E2)              Hash(E3 + E4)
                      /       \                  /       \
                 Hash(E1)   Hash(E2)        Hash(E3)   Hash(E4)
                    |          |               |          |
              Evidence-1   Evidence-2     Evidence-3   Evidence-4

Merkle Root Manifest:

{
  "protocol_id": "VP-BIO-QMS-IQ-001",
  "execution_date": "2026-02-16",
  "merkle_root": "f9e3d8b2a4c6f1e9d3b7a2c5f8e4d1b9a6c3a8f2e5d9b7a4c1e6d3b2a5c9f7e4",
  "leaf_count": 247,
  "evidence_artifacts": [
    {
      "evidence_id": "EV-2026-02-16-00001234",
      "sha256": "a3c5f8d2e1b4c9a7f3e8d2b1a5c7f9e3d8b2a4c6f1e9d3b7a2c5f8e4d1b9a6c3",
      "path": "VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-001/screenshot/step-4.2.1.png",
      "merkle_path": ["left", "left", "right"]
    }
  ],
  "signature": {
    "algorithm": "ECDSA-SHA256",
    "public_key_id": "validation-evidence-signing-key-2026",
    "signature": "3045022100e5b2c8f9a3d7e1b4c6a8f2d9e3b5c7a1f8e2d4b6c9a3f5e7d1b8c2a4f6e9d3022034f7a2e9d1b6c8a3f5e2d7b9c4a1f8e6d3b2a5c9f7e4d1b3a8c6f2e5d9b7a4c1",
    "signed_at": "2026-02-16T18:45:00Z",
    "signer": "U-8472"
  }
}

Verification Script:

#!/usr/bin/env python3
"""Verify evidence integrity via Merkle tree validation"""

import hashlib
import json
from pathlib import Path

def verify_merkle_tree(manifest_path: Path) -> bool:
    """Verify all evidence artifacts match Merkle root hash"""

    with open(manifest_path) as f:
        manifest = json.load(f)

    # Rebuild Merkle tree from leaf hashes
    leaf_hashes = []
    for artifact in manifest['evidence_artifacts']:
        # Download artifact from GCS
        artifact_data = download_from_gcs(artifact['path'])

        # Compute hash and verify match
        computed_hash = hashlib.sha256(artifact_data).hexdigest()
        if computed_hash != artifact['sha256']:
            print(f"INTEGRITY FAILURE: {artifact['evidence_id']}")
            print(f"  Expected: {artifact['sha256']}")
            print(f"  Computed: {computed_hash}")
            return False

        leaf_hashes.append(computed_hash)

    # Rebuild Merkle tree
    current_level = leaf_hashes
    while len(current_level) > 1:
        next_level = []
        for i in range(0, len(current_level), 2):
            left = current_level[i]
            right = current_level[i+1] if i+1 < len(current_level) else left
            parent = hashlib.sha256(f"{left}{right}".encode()).hexdigest()
            next_level.append(parent)
        current_level = next_level

    computed_root = current_level[0]

    if computed_root != manifest['merkle_root']:
        print(f"MERKLE ROOT MISMATCH")
        print(f"  Expected: {manifest['merkle_root']}")
        print(f"  Computed: {computed_root}")
        return False

    print(f"✓ Merkle tree integrity verified: {len(leaf_hashes)} artifacts")
    return True

3.4 Access Control and Audit Logging

Access Control Matrix:

Role	Create Evidence	Read Evidence	Modify Evidence	Delete Evidence
Validation Engineer	✓ (own tests only)	✓ (all)	✗ (immutable)	✗ (retention locked)
QA Reviewer	✗	✓ (all)	✗	✗
Quality Director	✗	✓ (all)	✗	✗
System Administrator	✗	✓ (all)	✗	✗
Evidence Collection Service	✓ (automated)	✓ (own uploads)	✗	✗
Auditor (FDA/External)	✗	✓ (all, read-only)	✗	✗

Access Audit Log:

Every evidence read operation generates an audit log entry:

{
  "event_type": "EVIDENCE_ACCESS",
  "timestamp": "2026-02-16T15:30:45.123456Z",
  "user_id": "U-9823",
  "user_name": "John Smith",
  "role": "QA_REVIEWER",
  "evidence_id": "EV-2026-02-16-00001234",
  "evidence_path": "VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-001/screenshot/step-4.2.1.png",
  "access_method": "web_portal",
  "ip_address": "192.168.1.45",
  "justification": "Review IQ test results for protocol VP-BIO-QMS-IQ-001"
}

3.5 Backup and Disaster Recovery

Backup Strategy:

Primary Storage: GCS multi-region (US) with 99.999% durability
Cross-Region Replication: Daily sync to GCS EU bucket (disaster recovery)
Offline Backup: Quarterly export to AWS S3 Glacier Deep Archive (regulatory requirement)
Local Archive: Annual DVD-R archival for air-gapped storage (7-year retention)

Recovery Time Objectives (RTO):

Scenario	RTO	Recovery Procedure
Single artifact corruption	15 minutes	Restore from GCS versioning
Bucket-level failure	4 hours	Failover to EU replica bucket
Regional GCS outage	8 hours	Restore from AWS S3 Glacier backup
Complete cloud provider failure	48 hours	Restore from offline DVD-R archive

4. Traceability Matrix Implementation

4.1 Traceability Matrix Structure

The validation traceability matrix provides bidirectional linkage across:

Forward Traceability: URS → FS → Design Spec → Test Protocol → Test Script → Evidence → Result Backward Traceability: Result → Evidence → Test Script → Test Protocol → Design Spec → FS → URS

Matrix Schema:

{
  "requirement_id": "URS-BIO-QMS-001",
  "requirement_text": "System shall enforce multi-factor authentication for all user logins",
  "requirement_type": "security",
  "functional_spec_id": "FS-AUTH-002",
  "functional_spec_section": "3.2.1 Multi-Factor Authentication",
  "design_spec_id": "DS-AUTH-MFA-001",
  "design_spec_section": "4.1 TOTP Implementation",
  "test_protocol_id": "VP-BIO-QMS-IQ-001",
  "test_case_id": "TC-IQ-002-MFA-ENROLLMENT",
  "test_steps": [
    {
      "step_id": "4.5.1",
      "step_description": "User enrolls TOTP device via QR code scan",
      "expected_result": "TOTP secret generated and stored in Vault",
      "test_script": "tests/validation/iq/test_mfa_enrollment.py::test_totp_qr_enrollment",
      "evidence_artifacts": [
        {
          "evidence_id": "EV-2026-02-16-00005678",
          "evidence_type": "screenshot",
          "path": "VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-002/screenshot/step-4.5.1-qr-code-displayed.png",
          "sha256": "b7e9f3a1d8c2b5e4a6f9d1c3b8e2a7f5d9c4b1e6a3f8d2c7b9e5a1f4d8c3b6e2"
        },
        {
          "evidence_id": "EV-2026-02-16-00005679",
          "evidence_type": "database_query",
          "path": "VP-BIO-QMS-IQ-001/2026-02-16/TC-IQ-002/db-query/vault-totp-seed-stored.json",
          "sha256": "c8f2a9e5d3b1c6a4f7e2d9b8c5a3f1e6d4b7a2c9f8e5d1b3a6c4f9e7d2b5a8c1"
        }
      ],
      "actual_result": "TOTP secret successfully stored in Vault with user_id association",
      "pass_fail": "pass",
      "execution_timestamp": "2026-02-16T11:15:30Z"
    }
  ],
  "coverage_status": "fully_covered",
  "gaps": []
}

4.2 Bidirectional Traceability Validation

Forward Trace Script:

#!/usr/bin/env python3
"""Validate forward traceability: URS → Evidence"""

def validate_forward_trace(requirement_id: str) -> bool:
    """Ensure requirement has complete trace to executed test evidence"""

    # Step 1: Lookup requirement in URS
    requirement = load_requirement(requirement_id)

    # Step 2: Find functional spec mapping
    fs_mapping = find_functional_spec(requirement_id)
    if not fs_mapping:
        print(f"❌ {requirement_id}: No functional spec mapping")
        return False

    # Step 3: Find design spec mapping
    ds_mapping = find_design_spec(fs_mapping['functional_spec_id'])
    if not ds_mapping:
        print(f"❌ {requirement_id}: No design spec mapping")
        return False

    # Step 4: Find test protocol/case mapping
    test_cases = find_test_cases(requirement_id)
    if not test_cases:
        print(f"❌ {requirement_id}: No test case coverage")
        return False

    # Step 5: Verify test execution evidence exists
    for test_case in test_cases:
        evidence = find_evidence(test_case['test_case_id'])
        if not evidence:
            print(f"❌ {test_case['test_case_id']}: No execution evidence")
            return False

        # Step 6: Verify evidence integrity (hash check)
        for artifact in evidence:
            if not verify_artifact_hash(artifact):
                print(f"❌ {artifact['evidence_id']}: Hash verification failed")
                return False

    print(f"✓ {requirement_id}: Complete forward trace with {len(test_cases)} test cases")
    return True

Backward Trace Script:

#!/usr/bin/env python3
"""Validate backward traceability: Evidence → URS"""

def validate_backward_trace(evidence_id: str) -> bool:
    """Ensure evidence artifact traces back to requirement"""

    # Step 1: Load evidence metadata
    evidence = load_evidence(evidence_id)

    # Step 2: Find parent test case
    test_case = find_test_case(evidence['test_case_id'])
    if not test_case:
        print(f"❌ {evidence_id}: No parent test case")
        return False

    # Step 3: Find test protocol
    protocol = load_protocol(test_case['protocol_id'])

    # Step 4: Find design spec
    design_spec = find_design_spec(protocol['design_spec_id'])
    if not design_spec:
        print(f"❌ {evidence_id}: No design spec mapping")
        return False

    # Step 5: Find functional spec
    fs = find_functional_spec(design_spec['fs_id'])
    if not fs:
        print(f"❌ {evidence_id}: No functional spec mapping")
        return False

    # Step 6: Find URS requirement
    requirement = find_requirement(fs['requirement_id'])
    if not requirement:
        print(f"❌ {evidence_id}: No URS requirement mapping")
        return False

    print(f"✓ {evidence_id}: Traces to {requirement['requirement_id']}")
    return True

4.3 Gap Detection

Automated Gap Analysis:

#!/usr/bin/env python3
"""Detect traceability gaps in validation matrix"""

def detect_traceability_gaps() -> dict:
    """Find untested requirements and orphan evidence"""

    gaps = {
        'untested_requirements': [],
        'unmapped_test_cases': [],
        'missing_evidence': [],
        'orphan_evidence': []
    }

    # Gap 1: Requirements without test cases
    all_requirements = load_all_requirements()
    for req in all_requirements:
        test_cases = find_test_cases(req['requirement_id'])
        if not test_cases:
            gaps['untested_requirements'].append({
                'requirement_id': req['requirement_id'],
                'requirement_text': req['text'],
                'severity': 'critical'
            })

    # Gap 2: Test cases without requirement mapping
    all_test_cases = load_all_test_cases()
    for tc in all_test_cases:
        if not tc.get('requirement_id'):
            gaps['unmapped_test_cases'].append({
                'test_case_id': tc['test_case_id'],
                'protocol_id': tc['protocol_id'],
                'severity': 'high'
            })

    # Gap 3: Test cases without execution evidence
    for tc in all_test_cases:
        evidence = find_evidence(tc['test_case_id'])
        if not evidence:
            gaps['missing_evidence'].append({
                'test_case_id': tc['test_case_id'],
                'protocol_id': tc['protocol_id'],
                'severity': 'critical'
            })

    # Gap 4: Evidence artifacts without test case mapping
    all_evidence = list_all_evidence()
    for ev in all_evidence:
        tc = find_test_case(ev['test_case_id'])
        if not tc:
            gaps['orphan_evidence'].append({
                'evidence_id': ev['evidence_id'],
                'path': ev['path'],
                'severity': 'medium'
            })

    return gaps

Gap Report Template:

# Validation Traceability Gap Analysis Report

**Generated:** 2026-02-16T16:00:00Z
**Report ID:** GAP-2026-02-16-001
**Validation Phase:** IQ

## Summary

| Gap Type | Count | Critical | High | Medium | Low |
|----------|-------|----------|------|--------|-----|
| Untested Requirements | 3 | 3 | 0 | 0 | 0 |
| Unmapped Test Cases | 2 | 0 | 2 | 0 | 0 |
| Missing Evidence | 1 | 1 | 0 | 0 | 0 |
| Orphan Evidence | 4 | 0 | 0 | 4 | 0 |
| **TOTAL** | **10** | **4** | **2** | **4** | **0** |

## Gap Details

### Untested Requirements (Critical)

1. **URS-BIO-QMS-047** - System shall enforce password complexity requirements
   - **Impact:** Security requirement not validated
   - **Remediation:** Add test case TC-IQ-015-PASSWORD-COMPLEXITY to IQ protocol
   - **Target Resolution:** 2026-02-17

2. **URS-BIO-QMS-089** - System shall generate audit trail for all GxP record modifications
   - **Impact:** Part 11 §11.10(e) requirement not validated
   - **Remediation:** Add test case TC-OQ-018-AUDIT-TRAIL-GXP to OQ protocol
   - **Target Resolution:** 2026-02-18

### Missing Evidence (Critical)

1. **TC-IQ-008-DATABASE-BACKUP** - Backup restoration test case
   - **Impact:** Cannot prove backup/restore functionality
   - **Remediation:** Re-execute test case with evidence collection enabled
   - **Target Resolution:** 2026-02-17

4.4 Traceability Matrix Formats

Excel Format (for QA review):

URS ID	Requirement	FS ID	DS ID	Protocol	Test Case	Evidence Count	Pass/Fail	Coverage
URS-001	MFA enforcement	FS-AUTH-002	DS-AUTH-MFA-001	VP-IQ-001	TC-IQ-002	12	PASS	✓
URS-002	Audit trail integrity	FS-AUDIT-001	DS-AUDIT-HMAC-001	VP-IQ-001	TC-IQ-009	8	PASS	✓
URS-047	Password complexity	—	—	—	—	0	—	✗

HTML Format (for inspector review):

Interactive table with hyperlinks to all artifacts
Click requirement ID → opens functional spec PDF
Click test case ID → opens protocol section
Click evidence count → lists all evidence artifacts with download links
Pass/fail status color-coded (green/red)
Coverage gaps highlighted in yellow

PDF Format (for regulatory submission):

Complete traceability matrix in table format
Appendices with all referenced documents
Evidence manifest with SHA-256 hashes
Digital signature page with QA approval

5. Deviation Management

5.1 Deviation Detection

Automated Deviation Detection:

Deviations are automatically detected during test execution when:

Expected Result Mismatch: Actual result differs from protocol specification
Test Script Failure: Automated test exits with non-zero code
Assertion Failure: Test framework assertion fails (e.g., assert expected == actual)
Performance Threshold Breach: Response time exceeds specified limit
Security Scan Finding: Vulnerability detected during validation testing
Configuration Drift: System configuration differs from validated baseline

Deviation Auto-Detection Script:

#!/usr/bin/env python3
"""Automatically detect and log validation deviations"""

def detect_deviation(test_result: dict) -> Optional[dict]:
    """Analyze test result for deviations"""

    deviation = None

    # Check 1: Pass/Fail status
    if test_result['pass_fail'] == 'fail':
        deviation = {
            'type': 'test_failure',
            'severity': 'critical',
            'description': f"Test case {test_result['test_case_id']} failed",
            'expected': test_result['expected_result'],
            'actual': test_result['actual_result']
        }

    # Check 2: Performance threshold
    if test_result.get('response_time_ms'):
        threshold = test_result.get('performance_threshold_ms', 2000)
        if test_result['response_time_ms'] > threshold:
            deviation = {
                'type': 'performance_degradation',
                'severity': 'major',
                'description': f"Response time {test_result['response_time_ms']}ms exceeds threshold {threshold}ms",
                'expected': f"<= {threshold}ms",
                'actual': f"{test_result['response_time_ms']}ms"
            }

    # Check 3: Security findings
    if test_result.get('security_scan_findings'):
        critical_findings = [f for f in test_result['security_scan_findings'] if f['severity'] == 'CRITICAL']
        if critical_findings:
            deviation = {
                'type': 'security_finding',
                'severity': 'critical',
                'description': f"{len(critical_findings)} critical security findings detected",
                'findings': critical_findings
            }

    if deviation:
        # Log deviation to database
        deviation_id = create_deviation_record(
            test_case_id=test_result['test_case_id'],
            deviation_type=deviation['type'],
            severity=deviation['severity'],
            description=deviation['description'],
            detected_at=datetime.utcnow()
        )

        # Trigger CAPA workflow if critical
        if deviation['severity'] == 'critical':
            create_capa(
                title=f"Validation Deviation: {test_result['test_case_id']}",
                description=deviation['description'],
                source_deviation_id=deviation_id
            )

        return deviation

    return None

5.2 Deviation Classification

Severity	Definition	Impact	Response Time	Approval Required
Critical	Test failure, system does not meet requirement	Validation cannot proceed, regulatory non-compliance risk	Immediate	QA Director + Quality Head
Major	Performance degradation, non-critical requirement gap	Validation can proceed with deviation approval	24 hours	QA Manager
Minor	Documentation discrepancy, cosmetic issue	Validation can proceed, document in final report	72 hours	Validation Lead

5.3 Deviation Impact Assessment Template

Deviation Report ID: DEV-2026-02-16-001

Test Case: TC-IQ-007-DATABASE-ENCRYPTION

Deviation Description:

Database column encryption verification failed for patient_notes field in clinical_records table. Expected AES-256-GCM encryption, found plaintext storage.

Detection Method: Automated - Database query inspection script

Detected By: U-8472 (Jane Doe, Validation Engineer)

Detection Timestamp: 2026-02-16T13:45:22Z

Severity Classification: Critical

Impact Assessment (15 Fields):

Field	Assessment
1. Regulatory Impact	HIPAA §164.312(a)(2)(iv) violation - PHI not encrypted at rest
2. Compliance Risk	High - FDA Part 11 §11.10(c) data integrity requirement at risk
3. Data Integrity Impact	Medium - Data readable but not tampered (integrity preserved via audit log)
4. Patient Safety Impact	None - No impact on clinical decision-making or patient care
5. Operational Impact	High - All validation testing halted pending fix
6. Timeline Impact	Validation delayed by 3 days (re-execution of 47 test cases required)
7. Resource Impact	24 engineer-hours for remediation + 16 hours re-testing
8. Scope of Affected Systems	Database layer only, application code correct (misconfigured Django field)
9. Root Cause (Preliminary)	Django model field defined as `TextField` instead of `EncryptedTextField`
10. Reproducibility	100% - Occurs on all records in `clinical_records` table
11. Workaround Available	No - Encryption required before validation can proceed
12. Previous Occurrences	None - First instance detected
13. Stakeholder Notification	QA Director, Quality Head, CISO, Validation Manager notified immediately
14. Regulatory Reporting	Not required (pre-production system, no patient data exposed)
15. CAPA Trigger	Yes - CAPA-2026-02-16-003 created for root cause analysis and preventive action

Recommended Resolution:

Update Django model: Change patient_notes = models.TextField() to patient_notes = EncryptedTextField()
Run database migration to encrypt existing records
Verify encryption with database inspection script
Re-execute TC-IQ-007 and all downstream test cases (47 total)
Update validation protocol to include pre-flight encryption verification check

Approval Workflow:

Role	Approver	Decision	Timestamp	Signature
Validation Lead	Jane Doe	Deviation confirmed	2026-02-16T14:00:00Z	[Digital Signature]
QA Manager	John Smith	Impact assessment approved	2026-02-16T14:15:00Z	[Digital Signature]
QA Director	Sarah Johnson	Resolution plan approved	2026-02-16T15:00:00Z	[Digital Signature]
Quality Head	Michael Chen	Proceed with remediation	2026-02-16T15:30:00Z	[Digital Signature]

5.4 CAPA Integration

Automatic CAPA Creation for Critical Deviations:

def create_capa_from_deviation(deviation_id: str):
    """Auto-create CAPA record for critical validation deviations"""

    deviation = load_deviation(deviation_id)

    if deviation['severity'] != 'critical':
        return  # Only critical deviations trigger CAPA

    capa_id = generate_capa_id()  # e.g., CAPA-2026-02-16-003

    capa_record = {
        'capa_id': capa_id,
        'title': f"Validation Deviation: {deviation['test_case_id']}",
        'description': deviation['description'],
        'source': 'validation_deviation',
        'source_reference': deviation_id,
        'category': 'quality_system',
        'initiated_by': deviation['detected_by'],
        'initiated_at': datetime.utcnow(),
        'status': 'open',
        'priority': 'high',
        'corrective_action': {
            'immediate': deviation.get('workaround', 'None available'),
            'root_cause_analysis_required': True,
            'preventive_action_required': True
        },
        'target_closure_date': datetime.utcnow() + timedelta(days=30)
    }

    # Insert into CAPA database
    save_capa(capa_record)

    # Link deviation to CAPA
    update_deviation(deviation_id, {'capa_id': capa_id})

    # Notify stakeholders
    send_notification(
        to=['qa-team@coditect.ai', 'quality-director@coditect.ai'],
        subject=f"Critical Validation Deviation: {deviation_id}",
        body=f"CAPA {capa_id} created for validation deviation in {deviation['test_case_id']}"
    )

5.5 Deviation Tracking and Resolution Timeline

Deviation Lifecycle:

Detected → Classified → Impact Assessed → Resolution Planned → CAPA Created (if critical) → Remediation → Verification → Closed

Timeline Requirements:

Severity	Initial Response	Impact Assessment	Resolution Plan	Remediation Complete	Verification	Total Timeline
Critical	1 hour	4 hours	8 hours	72 hours	48 hours	5 days max
Major	4 hours	24 hours	48 hours	7 days	3 days	14 days max
Minor	24 hours	72 hours	5 days	14 days	3 days	21 days max

Overdue Deviation Escalation:

50% of timeline elapsed → Email reminder to assignee
75% of timeline elapsed → Escalate to QA Manager
100% of timeline elapsed → Escalate to QA Director + Quality Head
120% of timeline elapsed → Executive escalation (CEO/CTO)

6. Evidence Package Assembly

6.1 Package Structure

Validation Evidence Package (ZIP file):

VP-BIO-QMS-IQ-001_Evidence-Package_2026-02-16.zip
├── 00-TABLE-OF-CONTENTS.pdf
├── 01-VALIDATION-PROTOCOL/
│   ├── VP-BIO-QMS-IQ-001_v1.0.pdf (signed)
│   └── VP-BIO-QMS-IQ-001_approval-signatures.json
├── 02-TEST-EXECUTION-SUMMARY/
│   ├── execution-summary.pdf
│   ├── traceability-matrix.xlsx
│   ├── traceability-matrix.html (interactive)
│   └── test-results-dashboard.png
├── 03-EVIDENCE-ARTIFACTS/
│   ├── TC-IQ-001-SYSTEM-LOGIN/
│   │   ├── execution-log.json
│   │   ├── screenshot-step-4.2.1.png
│   │   ├── screenshot-step-4.2.1.metadata.json
│   │   └── audit-trail-excerpt.json
│   ├── TC-IQ-002-MFA-ENROLLMENT/
│   │   └── [evidence files]
│   └── [additional test cases]
├── 04-DEVIATIONS/
│   ├── deviation-summary.pdf
│   ├── DEV-2026-02-16-001.pdf
│   └── CAPA-2026-02-16-003.pdf
├── 05-CONFIGURATION-BASELINE/
│   ├── system-configuration-snapshot.json
│   ├── software-versions.txt
│   └── database-schema.sql
├── 06-INTEGRITY-VERIFICATION/
│   ├── merkle-root-manifest.json (signed)
│   ├── evidence-manifest-SHA256.txt
│   └── integrity-verification-script.py
├── 07-APPROVAL-SIGNATURES/
│   ├── validation-lead-approval.pdf
│   ├── qa-review-approval.pdf
│   └── quality-head-approval.pdf
└── README.txt

Binder Generation Script:

#!/usr/bin/env python3
"""Generate PDF binder with hyperlinked table of contents"""

from PyPDF2 import PdfWriter, PdfReader
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
import io

def generate_toc_pdf(evidence_package: dict) -> bytes:
    """Generate table of contents PDF with hyperlinks"""

    buffer = io.BytesIO()
    c = canvas.Canvas(buffer, pagesize=letter)

    c.setFont("Helvetica-Bold", 16)
    c.drawString(50, 750, "Validation Evidence Package - Table of Contents")

    c.setFont("Helvetica", 10)
    c.drawString(50, 730, f"Protocol: {evidence_package['protocol_id']}")
    c.drawString(50, 715, f"Execution Date: {evidence_package['execution_date']}")
    c.drawString(50, 700, f"Total Test Cases: {evidence_package['test_case_count']}")

    y_position = 670
    c.setFont("Helvetica-Bold", 12)
    c.drawString(50, y_position, "Section")
    c.drawString(300, y_position, "Page")

    y_position -= 20
    c.setFont("Helvetica", 10)

    current_page = 2  # TOC is page 1
    for section in evidence_package['sections']:
        # Create hyperlink
        c.linkURL(
            url=f"#{section['section_id']}",  # Internal link to section
            rect=(50, y_position-5, 290, y_position+10),
            relative=0
        )

        c.drawString(50, y_position, section['title'])
        c.drawString(300, y_position, str(current_page))

        current_page += section['page_count']
        y_position -= 15

        if y_position < 100:  # New page if running out of space
            c.showPage()
            y_position = 750

    c.save()
    buffer.seek(0)
    return buffer.read()

def assemble_pdf_binder(evidence_package_path: str, output_path: str):
    """Assemble all PDFs into single binder with TOC"""

    package_metadata = load_package_metadata(evidence_package_path)

    writer = PdfWriter()

    # Add table of contents
    toc_pdf = generate_toc_pdf(package_metadata)
    toc_reader = PdfReader(io.BytesIO(toc_pdf))
    for page in toc_reader.pages:
        writer.add_page(page)

    # Add each section
    for section in package_metadata['sections']:
        section_pdf_path = f"{evidence_package_path}/{section['pdf_file']}"
        section_reader = PdfReader(section_pdf_path)

        # Add bookmark for section
        writer.add_outline_item(section['title'], len(writer.pages))

        for page in section_reader.pages:
            writer.add_page(page)

    # Write final binder
    with open(output_path, 'wb') as output_file:
        writer.write(output_file)

    print(f"✓ PDF binder generated: {output_path}")

6.3 Digital Signatures on Evidence Package

Package Signing Procedure:

Generate Package Manifest:
- List all files with SHA-256 hashes
- Include metadata (protocol ID, execution date, test case count)
- Merkle root hash of all evidence artifacts
Sign Manifest with Validation Key:
- ECDSA P-256 signature (per crypto-standards-policy.md)
- Signing key: validation-evidence-signing-key-2026 (HSM-stored)
- Signature algorithm: ECDSA-SHA256
Embed Signature in Package:
- Create SIGNATURE.json file with manifest + signature
- Include public key certificate for verification

Example Signature File:

{
  "package_id": "VP-BIO-QMS-IQ-001_2026-02-16",
  "manifest": {
    "protocol_id": "VP-BIO-QMS-IQ-001",
    "execution_date": "2026-02-16",
    "test_case_count": 47,
    "evidence_artifact_count": 247,
    "total_size_bytes": 1847293847,
    "merkle_root": "f9e3d8b2a4c6f1e9d3b7a2c5f8e4d1b9a6c3a8f2e5d9b7a4c1e6d3b2a5c9f7e4",
    "file_hashes": {
      "00-TABLE-OF-CONTENTS.pdf": "a3c5f8d2e1b4c9a7f3e8d2b1a5c7f9e3d8b2a4c6f1e9d3b7a2c5f8e4d1b9a6c3",
      "01-VALIDATION-PROTOCOL/VP-BIO-QMS-IQ-001_v1.0.pdf": "b7e9f3a1d8c2b5e4a6f9d1c3b8e2a7f5d9c4b1e6a3f8d2c7b9e5a1f4d8c3b6e2"
    }
  },
  "signature": {
    "algorithm": "ECDSA-SHA256",
    "public_key_id": "validation-evidence-signing-key-2026",
    "public_key_pem": "-----BEGIN PUBLIC KEY-----\nMFkwEwYHKoZIzj0CAQYIKoZIzj0DAQcDQgAE...\n-----END PUBLIC KEY-----",
    "signature_hex": "3045022100e5b2c8f9a3d7e1b4c6a8f2d9e3b5c7a1f8e2d4b6c9a3f5e7d1b8c2a4f6e9d3022034f7a2e9d1b6c8a3f5e2d7b9c4a1f8e6d3b2a5c9f7e4d1b3a8c6f2e5d9b7a4c1",
    "signed_at": "2026-02-16T18:00:00Z",
    "signer_id": "U-8472",
    "signer_name": "Jane Doe",
    "signer_role": "Validation Lead"
  }
}

Verification Script:

#!/usr/bin/env python3
"""Verify digital signature on evidence package"""

from cryptography.hazmat.primitives import hashes, serialization
from cryptography.hazmat.primitives.asymmetric import ec
import json

def verify_package_signature(package_path: str) -> bool:
    """Verify ECDSA signature on evidence package manifest"""

    # Load signature file
    with open(f"{package_path}/SIGNATURE.json") as f:
        sig_data = json.load(f)

    # Load public key
    public_key = serialization.load_pem_public_key(
        sig_data['signature']['public_key_pem'].encode()
    )

    # Reconstruct manifest bytes for verification
    manifest_bytes = json.dumps(
        sig_data['manifest'],
        sort_keys=True
    ).encode()

    # Verify signature
    signature_bytes = bytes.fromhex(sig_data['signature']['signature_hex'])

    try:
        public_key.verify(
            signature_bytes,
            manifest_bytes,
            ec.ECDSA(hashes.SHA256())
        )
        print("✓ Package signature valid")
        return True
    except Exception as e:
        print(f"❌ Signature verification failed: {e}")
        return False

6.4 Package Version Control

Version Scheme: {Protocol-ID}_v{Version}_{Execution-Date}

Example: VP-BIO-QMS-IQ-001_v1.0_2026-02-16.zip

Version Control Rules:

v1.0 - Initial evidence package assembly
v1.1 - Minor corrections (typo fixes, re-exports) - no re-testing required
v2.0 - Major revision (test re-execution) - requires new approval signatures

Change Log:

# Evidence Package Change Log

## VP-BIO-QMS-IQ-001_v1.1_2026-02-16

**Changes from v1.0:**

- Corrected typo in Table of Contents (page 2, section title)
- Re-generated traceability matrix HTML with corrected hyperlinks
- No changes to test execution evidence or results

**Approval:** Validation Lead (Jane Doe) - 2026-02-17T10:00:00Z
**Rationale:** Administrative correction, no impact on validation conclusions

6.5 Inspector-Ready Format (15-Minute Retrieval Guarantee)

Retrieval Guarantee Implementation:

Evidence Portal Web Application:
- Search by protocol ID, test case ID, requirement ID
- Filter by date range, pass/fail status, deviation status
- One-click download of evidence package or individual artifacts
- Preview screenshots and logs inline (no download required)
Pre-Generated Inspector Packages:
- Quarterly export of all validation packages to DVD-R
- Labeled and stored in fireproof safe (accessible to QA team)
- Index document listing all packages and contents
GCS Bucket Fast Retrieval:
- All evidence stored in STANDARD storage class (no retrieval delay)
- Parallel download support (multiple artifacts simultaneously)
- Pre-signed URLs for inspector access (no authentication required)
Automated Retrieval Script:

#!/bin/bash
# Retrieve any validation artifact within 15 minutes

PROTOCOL_ID="$1"
RETRIEVAL_DIR="/tmp/inspector-package-${PROTOCOL_ID}"

echo "Retrieving evidence package for ${PROTOCOL_ID}..."

# Download from GCS (parallel, 10 threads)
gsutil -m cp -r \
  "gs://coditect-bio-qms-validation-evidence/${PROTOCOL_ID}/*" \
  "${RETRIEVAL_DIR}/"

# Verify integrity
python3 /opt/validation/verify-evidence-integrity.py "${RETRIEVAL_DIR}"

# Generate PDF binder
python3 /opt/validation/generate-pdf-binder.py \
  --input "${RETRIEVAL_DIR}" \
  --output "${RETRIEVAL_DIR}/${PROTOCOL_ID}_Evidence-Package.pdf"

echo "✓ Evidence package ready at ${RETRIEVAL_DIR}"
echo "  Retrieval time: $(date -d@$SECONDS -u +%M:%S)"

Performance Benchmark:

Protocol with 47 test cases, 247 evidence artifacts (1.8 GB total)
Retrieval time: 8 minutes 32 seconds (well under 15-minute guarantee)
PDF binder generation: 2 minutes 15 seconds
Total: 10 minutes 47 seconds

7. Regulatory Submission Format

7.1 FDA Computer System Validation Package Requirements

FDA Expectations (per Guidance for Industry: Computerized Systems Used in Clinical Investigations):

Validation Plan - High-level strategy and scope
Requirements Specification - URS documenting functional and non-functional requirements
Design Specification - System architecture and design decisions
Test Protocols - IQ/OQ/PQ protocols with detailed test cases
Test Results - Executed protocols with evidence of pass/fail for each test
Traceability Matrix - Requirements → Tests → Results linkage
Deviations and Resolutions - All deviations with impact assessments and CAPAs
Validation Summary Report - Executive summary and validation conclusions

BIO-QMS Evidence Package Mapping to FDA Requirements:

FDA Requirement	BIO-QMS Document	Location in Evidence Package
Validation Plan	Validation Master Plan	`01-VALIDATION-PROTOCOL/Validation-Master-Plan_v1.0.pdf`
Requirements Specification	User Requirements Specification (URS)	`01-VALIDATION-PROTOCOL/URS-BIO-QMS_v1.0.pdf`
Design Specification	System Design Document (SDD)	`05-CONFIGURATION-BASELINE/SDD-BIO-QMS_v1.0.pdf`
Test Protocols	IQ/OQ/PQ Protocols	`01-VALIDATION-PROTOCOL/VP-BIO-QMS-{IQ
Test Results	Evidence artifacts + execution logs	`03-EVIDENCE-ARTIFACTS/`
Traceability Matrix	Requirements-to-Tests-to-Evidence	`02-TEST-EXECUTION-SUMMARY/traceability-matrix.xlsx`
Deviations	Deviation reports + CAPAs	`04-DEVIATIONS/`
Validation Summary Report	VSR (covered in D.2.5)	`07-APPROVAL-SIGNATURES/Validation-Summary-Report_v1.0.pdf`

7.2 eCTD (Electronic Common Technical Document) Compatibility

eCTD Module 3.2.P.3.4 - Control of Critical Steps and Intermediates (Manufacturing Process Validation):

While BIO-QMS is a software system (not a pharmaceutical manufacturing process), the eCTD structure provides a recognized format for regulatory submissions.

eCTD-Compatible Evidence Package Structure:

module-3/
└── 3-2-p-3-4-control-of-critical-steps/
    ├── 3-2-p-3-4-validation-summary.pdf
    ├── 3-2-p-3-4-1-validation-plan.pdf
    ├── 3-2-p-3-4-2-requirements-specification.pdf
    ├── 3-2-p-3-4-3-design-specification.pdf
    ├── 3-2-p-3-4-4-test-protocols.pdf
    ├── 3-2-p-3-4-5-test-results/
    │   ├── iq-results.pdf
    │   ├── oq-results.pdf
    │   └── pq-results.pdf
    ├── 3-2-p-3-4-6-traceability-matrix.pdf
    └── 3-2-p-3-4-7-deviations.pdf

eCTD Metadata (for electronic submission portal):

<?xml version="1.0" encoding="UTF-8"?>
<ectd:ectd xmlns:ectd="http://www.ich.org/ectd">
  <ectd:module-3>
    <ectd:quality-overall-summary>
      <ectd:manufacturing-process-validation>
        <ectd:title>Computer System Validation - BIO-QMS Platform</ectd:title>
        <ectd:document-date>2026-02-16</ectd:document-date>
        <ectd:document-version>1.0</ectd:document-version>
        <ectd:applicant>AZ1.AI Inc.</ectd:applicant>
        <ectd:validation-type>Prospective</ectd:validation-type>
        <ectd:system-name>CODITECT Biosciences Quality Management System</ectd:system-name>
        <ectd:regulatory-standard>FDA 21 CFR Part 11</ectd:regulatory-standard>
      </ectd:manufacturing-process-validation>
    </ectd:quality-overall-summary>
  </ectd:module-3>
</ectd:ectd>

7.3 Section Numbering and Organization per FDA Guidance

Evidence Package Outline (FDA-Aligned Numbering):

EXECUTIVE SUMMARY
1 Validation Scope
2 Validation Approach
3 Test Execution Summary
4 Validation Conclusion

SYSTEM DESCRIPTION
1 System Overview
2 Intended Use
3 User Roles
4 Regulatory Classification
5 Software Configuration

VALIDATION PLANNING
1 Validation Master Plan
2 Validation Strategy (Prospective/Concurrent/Retrospective)
3 Risk Assessment
4 Validation Team and Responsibilities

REQUIREMENTS SPECIFICATION
1 User Requirements (URS)
2 Functional Specifications
3 Design Specifications
4 Requirements Traceability

VALIDATION PROTOCOLS
1 Installation Qualification (IQ) Protocol
2 Operational Qualification (OQ) Protocol
3 Performance Qualification (PQ) Protocol
4 Test Case Design Rationale

VALIDATION EXECUTION
1 Test Execution Logs
2 Evidence Artifacts
3 Pass/Fail Summary
4 Traceability Matrix

DEVIATIONS AND CORRECTIVE ACTIONS
1 Deviation Summary
2 Deviation Reports (Individual)
3 CAPA Records
4 Resolution Evidence

VALIDATION CONCLUSIONS
1 Validation Summary Report
2 System Fitness for Intended Use
3 Recommendations
4 Periodic Review Schedule

APPENDICES
1 Approval Signatures
2 Configuration Baseline
3 Integrity Verification
4 Regulatory Standards Matrix

8. Cross-References

This document references and integrates with:

D.2.1: Validation Test Protocols - Protocol development procedures
D.2.2: Validation Record Controls - Electronic record integrity requirements
D.2.3: Validation Signature Controls - E-signature binding to evidence
D.2.5: Validation Review and Approval - QA review and VSR procedures
crypto-standards-policy.md - Cryptographic algorithms for evidence signing
17-e-signature-architecture.md - ECDSA P-256 signature implementation

Document ID: CODITECT-BIO-VAL-004 Version: 1.0.0 Classification: Internal - Restricted Next Review Date: 2027-02-16 Policy Owner: Validation Manager Document Location: docs/compliance/validation-evidence-package.md Approval Status: Draft (pending QA approval)

Confidentiality Notice: This document contains proprietary information and is intended solely for authorized personnel of CODITECT Biosciences. Unauthorized distribution is prohibited.

END OF DOCUMENT

Document Control​

Approval History​

Revision History​

Distribution List​

Review Schedule​

1. Purpose and Scope​

1.1 Purpose​

1.2 Scope​

1.3 Audience​

2. Evidence Collection Framework​

2.1 Evidence Types​

2.2 Evidence Metadata Schema​

2.3 Automated Evidence Collection Scripts​

2.3.1 Test Execution Evidence Script​

2.3.2 Configuration Capture Script​

2.3.3 Audit Trail Evidence Extractor​

2.4 Manual Evidence Collection Procedures​

2.4.1 Screenshot Capture Procedure​

2.4.2 Database Query Evidence Procedure​

3. Evidence Storage Architecture​

3.1 Tamper-Evident Storage Requirements​

3.2 Cloud Storage Configuration​

3.3 Integrity Chain Implementation​

3.4 Access Control and Audit Logging​

3.5 Backup and Disaster Recovery​

4. Traceability Matrix Implementation​

4.1 Traceability Matrix Structure​

4.2 Bidirectional Traceability Validation​

4.3 Gap Detection​

4.4 Traceability Matrix Formats​

5. Deviation Management​

5.1 Deviation Detection​

5.2 Deviation Classification​

5.3 Deviation Impact Assessment Template​

5.4 CAPA Integration​

5.5 Deviation Tracking and Resolution Timeline​

6. Evidence Package Assembly​

6.1 Package Structure​

6.2 PDF Binder Generation with Hyperlinked Navigation​

6.3 Digital Signatures on Evidence Package​

6.4 Package Version Control​

6.5 Inspector-Ready Format (15-Minute Retrieval Guarantee)​

7. Regulatory Submission Format​

7.1 FDA Computer System Validation Package Requirements​

7.2 eCTD (Electronic Common Technical Document) Compatibility​

7.3 Section Numbering and Organization per FDA Guidance​

8. Cross-References​

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Approval History

Revision History

Distribution List

Review Schedule

1. Purpose and Scope

1.1 Purpose

1.2 Scope

1.3 Audience

2. Evidence Collection Framework

2.1 Evidence Types

2.2 Evidence Metadata Schema

2.3 Automated Evidence Collection Scripts

2.3.1 Test Execution Evidence Script

2.3.2 Configuration Capture Script

2.3.3 Audit Trail Evidence Extractor

2.4 Manual Evidence Collection Procedures

2.4.1 Screenshot Capture Procedure

2.4.2 Database Query Evidence Procedure

3. Evidence Storage Architecture

3.1 Tamper-Evident Storage Requirements

3.2 Cloud Storage Configuration

3.3 Integrity Chain Implementation

3.4 Access Control and Audit Logging

3.5 Backup and Disaster Recovery

4. Traceability Matrix Implementation

4.1 Traceability Matrix Structure

4.2 Bidirectional Traceability Validation

4.3 Gap Detection

4.4 Traceability Matrix Formats

5. Deviation Management

5.1 Deviation Detection

5.2 Deviation Classification

5.3 Deviation Impact Assessment Template

5.4 CAPA Integration

5.5 Deviation Tracking and Resolution Timeline

6. Evidence Package Assembly

6.1 Package Structure

6.2 PDF Binder Generation with Hyperlinked Navigation

6.3 Digital Signatures on Evidence Package

6.4 Package Version Control

6.5 Inspector-Ready Format (15-Minute Retrieval Guarantee)

7. Regulatory Submission Format

7.1 FDA Computer System Validation Package Requirements

7.2 eCTD (Electronic Common Technical Document) Compatibility

7.3 Section Numbering and Organization per FDA Guidance

8. Cross-References

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