IACUC Protocol Drafter

ID: 105
Name: IACUC Protocol Drafter
Description: Draft Institutional Animal Care and Use Committee (IACUC) protocol applications, especially the justification section for the "3Rs principles" (Replacement, Reduction, Refinement).

Requirements

• Python 3.8+
• No additional dependencies (uses standard library)

Usage

# Generate local file
python skills/iacuc-protocol-drafter/scripts/main.py --input protocol_input.json --output iacuc_protocol.txt

# Use stdin/stdout
cat protocol_input.json | python skills/iacuc-protocol-drafter/scripts/main.py

Parameters

Input Format (JSON)

{
  "title": "Experiment Title",
  "principal_investigator": "Principal Investigator Name",
  "institution": "Research Institution Name",
  "species": "Experimental Animal Species",
  "number_of_animals": 50,
  "procedure_description": "Brief description of experimental procedures",
  "pain_category": "B",
  "justification": {
    "replacement": {
      "alternatives_considered": ["In vitro experiments", "Computer simulation"],
      "why_animals_needed": "Reasons why animals must be used"
    },
    "reduction": {
      "sample_size_calculation": "Sample size calculation method and rationale",
      "minimization_strategies": "Strategies to minimize animal numbers"
    },
    "refinement": {
      "pain_management": "Pain management measures",
      "housing_enrichment": "Housing environment optimization",
      "humane_endpoints": "Humane endpoint setting"
    }
  }
}

Output

Generate IACUC-standard application text, including a complete 3Rs principles justification section.

Templates

Built-in standard templates cover:

• Replacement: Justification for why live animals must be used
• Reduction: Explanation of statistical basis for sample size calculation
• Refinement: Description of measures to reduce pain and stress

Notes

• Generated content should be used as a draft and adjusted according to actual conditions
• It is recommended to consult your institution's IACUC office for specific format requirements
• Ensure all animal experiments comply with local regulations and institutional policies

Risk Assessment

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support