Drug Interaction Checker

Check for interactions between multiple medications, including severity classification and mechanism explanations.

Features

• Multi-drug analysis: Check interactions between 2+ medications simultaneously
• Severity classification: Critical / Major / Moderate / Minor / Unknown
• Mechanism explanation: Pharmacological basis for each interaction
• Clinical guidance: Recommendations for management

Severity Levels

Level	Description	Action Required
Critical	Life-threatening interaction	Absolute contraindication
Major	Significant risk, may need medical intervention	Avoid combination or monitor closely
Moderate	Moderate risk, may require dose adjustment	Monitor for adverse effects
Minor	Mild interaction, unlikely to cause issues	Be aware, usually acceptable
Unknown	Insufficient data	Proceed with caution

Usage

Python Script

python scripts/main.py --drugs "Warfarin" "Aspirin" "Ibuprofen"

As a Module

from scripts.main import check_interactions

result = check_interactions(["Metformin", "Simvastatin", "Amlodipine"])

Parameters

Parameter	Type	Default	Required	Description
--drugs	list	-	Yes	List of drug names (generic or brand names accepted)
--format	string	text	No	Output format (text, json, markdown)
--include-mechanism	flag	true	No	Include pharmacological mechanism
--include-management	flag	true	No	Include clinical recommendations
--output, -o	string	-	No	Output file path

Output Format

{
  "drugs_checked": ["Drug A", "Drug B"],
  "interactions": [
    {
      "drug_pair": ["Drug A", "Drug B"],
      "severity": "Major",
      "mechanism": "Pharmacodynamic synergism...",
      "effect": "Increased bleeding risk",
      "recommendation": "Avoid combination or monitor INR closely"
    }
  ],
  "summary": {
    "critical": 0,
    "major": 1,
    "moderate": 0,
    "minor": 0
  }
}

Data Sources

This skill uses a curated drug interaction database stored in references/interactions_db.json. The database includes:

• FDA-approved drug interaction data
• Known metabolic pathways (CYP450 enzymes)
• Pharmacodynamic interactions
• Common supplement interactions

Limitations

• Database may not include all possible drug combinations
• Always consult healthcare professionals for medical decisions
• Does not account for patient-specific factors (age, renal function, etc.)
• Not a substitute for professional medical advice

Technical Difficulty

High - Requires extensive pharmacological knowledge database, accurate severity classification, and clear mechanism explanations.

References

See references/ directory for:

• interactions_db.json - Drug interaction database
• severity_criteria.md - Classification criteria
• cyp450_substrates.json - Metabolic pathway data

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access	No external API calls	Low
File System Access	Read input files, write output files	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

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

# Python dependencies
pip install -r requirements.txt

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