drug-drug-interaction-analysis

Drug-Drug Interaction Analysis

Analyze potential drug-drug interactions (DDI) for medication safety assessment.

When to Use

• Checking interactions between prescribed medications
• Evaluating DDI risk for polypharmacy patients
• Understanding interaction mechanisms (CYP enzymes, shared targets)
• Clinical decision support for drug combinations

Workflow

Step 1: Resolve Drug Names to KEGG IDs

import requests

KEGG_API = "https://rest.kegg.jp"

def find_drug_id(drug_name: str) -> str:
    """Find KEGG drug ID from drug name."""
    response = requests.get(f"{KEGG_API}/find/drug/{drug_name}")
    if response.ok and response.text.strip():
        # Parse first result: "dr:D00109\tAspirin..."
        line = response.text.strip().split('\n')[0]
        return line.split('\t')[0]  # Returns "dr:D00109"
    return None

Step 2: Query KEGG DDI API

def get_ddi(drug_ids: list) -> list:
    """Query KEGG DDI for multiple drugs."""
    ids = "+".join(drug_ids)
    response = requests.get(f"{KEGG_API}/ddi/{ids}")
    interactions = []
    for line in response.text.strip().split('\n'):
        if line:
            parts = line.split('\t')
            interactions.append({
                "drug_a": parts[0],
                "drug_b": parts[1],
                "severity": parts[2],
                "mechanism": parts[3] if len(parts) > 3 else ""
            })
    return interactions

Step 3: Get Detailed Drug Information

def get_drug_info(drug_id: str) -> dict:
    """Get detailed drug information from KEGG."""
    response = requests.get(f"{KEGG_API}/get/{drug_id}")
    info = {"id": drug_id, "targets": [], "enzymes": []}
    for line in response.text.split('\n'):
        if line.startswith("NAME"):
            info["name"] = line.split(maxsplit=1)[1].strip()
        elif line.startswith("TARGET"):
            info["targets"].append(line.split(maxsplit=1)[1])
        elif line.startswith("METABOLISM"):
            info["enzymes"].append(line.split(maxsplit=1)[1])
    return info