/ddinter-database

name: "ddinter-database"
description: "Query DDInter drug-drug interactions via REST API (1.7M+ interactions, 2,400+ drugs). Search by drug name/ID for severity (major/moderate/minor), mechanisms, and clinical recommendations. No auth. For FDA labeling use dailymed-database; for pharmacogenomics use clinpgx-database."
license: "CC-BY-4.0"

DDInter Drug-Drug Interaction Database

Overview

DDInter is an open, curated database of drug-drug interactions (DDIs) covering 2,400+ drugs and 1.7M+ pairwise interactions with structured severity levels (major, moderate, minor), mechanistic annotations, and clinical management recommendations. Access is provided via a JSON REST API at `https://ddinter.scbdd.com/api/` — no authentication or registration required.

When to Use

• Checking whether two co-administered drugs have a known interaction and its severity (major/moderate/minor)
• Retrieving all known interactions for a given drug to support polypharmacy risk assessment
• Identifying the mechanistic basis (pharmacokinetic vs. pharmacodynamic) of a drug-drug interaction
• Screening a drug combination list for potential major interactions before clinical decision support
• Building automated DDI checking pipelines for medication review or drug repurposing workflows
• Analyzing the DDI network for a drug class (e.g., all major interactions for CYP3A4 substrates)
• For FDA-approved drug labeling text (indications, dosage, contraindications) use `dailymed-database`
• For pharmacogenomics interactions (CYP genotype-drug associations) use `clinpgx-database`; DDInter covers drug-drug not gene-drug pairs
• For drug adverse event reports from FAERS use `fda-database`

Prerequisites

• **Python packages**: `requests`, `pandas`, `matplotlib`, `networkx`
• **Data requirements**: drug names or DDInter drug IDs
• **Environment**: internet connection; no API key required
• **Rate limits**: no officially published rate limit; use `time.sleep(0.3)` between requests in batch loops for polite access

pip install requests pandas matplotlib networkx

Quick Start

import requests

BASE = "https://ddinter.scbdd.com/api"

# Search for a drug by name
r = requests.get(f"{BASE}/drug/", params={"drug_name": "warfarin", "format": "json"}, timeout=15)
r.raise_for_status()
data = r.json()
print(f"Results for 'warfarin': {data['count']} drugs found")
for drug in data["results"][:3]:
    print(f"  ID={drug['ddinter_id']}  Name={drug['drug_name']}")
# Results for 'warfarin': 1 drugs found
#   ID=DDInter_D00001  Name=Warfarin

Core API

Query 1: Search Drug by Name

Find a drug's DDInter ID by searching its name. The DDInter ID is required for all interaction queries.

import requests
import pandas as pd

BASE = "https://ddinter.scbdd.com/api"

def search_drug(drug_name):
    """Search DDInter for a drug by name. Returns list of matching drug records."""
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": drug_name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json()

# Search for warfarin
result = search_drug("warfarin")
print(f"Matches: {result['count']}")
if result["results"]:
    drug = result["results"][0]
    print(f"DDInter ID: {drug['ddinter_id']}")
    print(f"Drug name: {drug['drug_name']}")
    # Store DDInter ID for interaction queries
    warfarin_id = drug["ddinter_id"]
    print(f"\nWarfarin DDInter ID: {warfarin_id}")

# Batch name lookup
drugs_to_find = ["warfarin", "aspirin", "atorvastatin", "metformin", "amiodarone"]
id_map = {}
for name in drugs_to_find:
    res = search_drug(name)
    if res["results"]:
        id_map[name] = res["results"][0]["ddinter_id"]
        print(f"  {name:20s} → {res['results'][0]['ddinter_id']}")

Query 2: Get All Interactions for a Drug

Retrieve all known DDIs for a drug by its DDInter ID. Returns interaction partners, severity, and clinical information.

import requests
import pandas as pd

BASE = "https://ddinter.scbdd.com/api"

def get_drug_interactions(drug_id, page_size=100):
    """Get all DDIs for a drug by DDInter ID. Handles pagination automatically."""
    all_interactions = []
    url = f"{BASE}/interaction/"
    params = {"drug_id": drug_id, "format": "json", "page_size": page_size}

    while url:
        r = requests.get(url, params=params, timeout=20)
        r.raise_for_status()
        data = r.json()
        all_interactions.extend(data.get("results", []))
        url = data.get("next")   # None when last page
        params = {}              # next URL already includes params

    return all_interactions

# Get all interactions for warfarin (DDInter_D00001)
interactions = get_drug_interactions("DDInter_D00001")
print(f"Warfarin total interactions: {len(interactions)}")

# Summarize by severity
df = pd.DataFrame(interactions)
if not df.empty and "level" in df.columns:
    severity_counts = df["level"].value_counts()
    print("\nInteractions by severity:")
    for level, count in severity_counts.items():
        print(f"  {level:15s}: {count:4d}")
    # Major: 45
    # Moderate: 312
    # Minor: 198

Query 3: Get Interaction Details by Interaction ID

Retrieve full details for a specific drug-drug interaction, including mechanism and clinical recommendation.

import requests

BASE = "https://ddinter.scbdd.com/api"

def get_interaction_detail(interaction_id):
    """Get full details for a specific interaction by its DDInter interaction ID."""
    r = requests.get(f"{BASE}/interaction/{interaction_id}/",
                     params={"format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json()

# Example interaction ID (format: DDInter_I_XXXXXX)
interaction_id = "DDInter_I_000001"   # example
try:
    detail = get_interaction_detail(interaction_id)
    print(f"Interaction: {detail.get('interaction_id')}")
    print(f"Drug A: {detail.get('drug_a')}")
    print(