Ddinter Database

pip install requests pandas matplotlib networkx

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

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']}")

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

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(f"Drug B: {detail.get('drug_b')}")
    print(f"Severity: {detail.get('level')}")
    print(f"Mechanism: {detail.get('mechanism', 'Not specified')[:200]}")
    print(f"Recommendation: {detail.get('recommendation', 'Not specified')[:200]}")
    print(f"PK type: {detail.get('pharmacokinetic_type', 'N/A')}")
    print(f"PD type: {detail.get('pharmacodynamic_type', 'N/A')}")
except Exception as e:
    print(f"Note: Use a valid interaction ID from get_drug_interactions() results. Error: {e}")

import requests

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

def check_drug_pair(drug_id_1, drug_id_2):
    """Check interactions between two specific drugs by their DDInter IDs."""
    r = requests.get(f"{BASE}/between/",
                     params={"drug1": drug_id_1, "drug2": drug_id_2, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json()

def find_drug_id(drug_name):
    """Helper: resolve drug name to DDInter ID."""
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": drug_name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    results = r.json()["results"]
    return results[0]["ddinter_id"] if results else None

# Check warfarin + aspirin interaction
warfarin_id = find_drug_id("warfarin")
aspirin_id = find_drug_id("aspirin")

if warfarin_id and aspirin_id:
    interactions = check_drug_pair(warfarin_id, aspirin_id)
    count = interactions.get("count", 0)
    print(f"Warfarin + Aspirin: {count} interaction(s) found")
    for ix in interactions.get("results", []):
        print(f"  Severity: {ix.get('level')}")
        print(f"  Mechanism: {ix.get('mechanism', 'N/A')[:200]}")
        print(f"  Recommendation: {ix.get('recommendation', 'N/A')[:200]}")
else:
    print(f"Could not resolve drug IDs: warfarin={warfarin_id}, aspirin={aspirin_id}")

import requests
import pandas as pd

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

def get_major_interactions(drug_id):
    """Get only major-severity interactions for a drug."""
    all_interactions = []
    r = requests.get(f"{BASE}/interaction/",
                     params={"drug_id": drug_id, "format": "json", "page_size": 200},
                     timeout=20)
    r.raise_for_status()
    data = r.json()
    all_interactions.extend(data.get("results", []))

    # Filter to major severity
    major = [ix for ix in all_interactions
             if ix.get("level", "").lower() == "major"]
    return major

# Get major interactions for amiodarone (known high-interaction drug)
drug_id = "DDInter_D00023"   # example amiodarone ID; resolve with search_drug()
major_ixs = get_major_interactions(drug_id)
print(f"Major interactions: {len(major_ixs)}")

if major_ixs:
    df = pd.DataFrame(major_ixs)
    # Show drug partners and mechanism type
    for col in ["drug_a", "drug_b", "level", "pharmacokinetic_type"]:
        if col in df.columns:
            print(f"  {col}: {df[col].value_counts().head(3).to_dict()}")
    df.to_csv("amiodarone_major_interactions.csv", index=False)
    print("Saved: amiodarone_major_interactions.csv")

import requests
import time
import itertools
import pandas as pd

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

def find_drug_id(drug_name):
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": drug_name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    results = r.json()["results"]
    return (results[0]["ddinter_id"], results[0]["drug_name"]) if results else (None, None)

def check_pair(id1, id2):
    r = requests.get(f"{BASE}/between/",
                     params={"drug1": id1, "drug2": id2, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json().get("results", [])

# Medication list to screen
medication_names = ["warfarin", "aspirin", "atorvastatin", "metformin", "amiodarone"]

# Resolve to DDInter IDs
id_map = {}
for name in medication_names:
    ddid, resolved_name = find_drug_id(name)
    if ddid:
        id_map[name] = (ddid, resolved_name)
        print(f"  {name:20s} → {ddid}")
    time.sleep(0.3)

# Check all pairs
flagged = []
for (n1, (id1, rn1)), (n2, (id2, rn2)) in itertools.combinations(id_map.items(), 2):
    ixs = check_pair(id1, id2)
    for ix in ixs:
        level = ix.get("level", "unknown")
        if level.lower() in ("major", "moderate"):
            flagged.append({
                "drug_1": rn1,
                "drug_2": rn2,
                "severity": level,
                "mechanism": ix.get("mechanism", "")[:100],
            })
    time.sleep(0.3)

df = pd.DataFrame(flagged)
print(f"\nFlagged interactions: {len(df)}")
if not df.empty:
    print(df.to_string(index=False))
    df.to_csv("polypharmacy_screening.csv", index=False)
    print("Saved: polypharmacy_screening.csv")

import requests
import time
import itertools
import pandas as pd
import networkx as nx
import matplotlib.pyplot as plt

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

def find_drug_id(drug_name):
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": drug_name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    results = r.json()["results"]
    return (results[0]["ddinter_id"], results[0]["drug_name"]) if results else (None, None)

def check_pair(id1, id2):
    r = requests.get(f"{BASE}/between/",
                     params={"drug1": id1, "drug2": id2, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json().get("results", [])

SEVERITY_COLORS = {"major": "#D32F2F", "moderate": "#F57C00", "minor": "#388E3C"}

# Drug list
drugs = ["warfarin", "aspirin", "atorvastatin", "fluconazole", "amiodarone"]
id_map = {}
for name in drugs:
    ddid, rname = find_drug_id(name)
    if ddid:
        id_map[name] = (ddid, rname)
    time.sleep(0.3)

# Build network
G = nx.Graph()
for name, (ddid, rname) in id_map.items():
    G.add_node(rname)

edge_colors = []
for (n1, (id1, rn1)), (n2, (id2, rn2)) in itertools.combinations(id_map.items(), 2):
    ixs = check_pair(id1, id2)
    for ix in ixs:
        level = ix.get("level", "minor").lower()
        G.add_edge(rn1, rn2, severity=level, weight=3 if level == "major" else 1)
    time.sleep(0.3)

# Visualize
fig, ax = plt.subplots(figsize=(9, 7))
pos = nx.spring_layout(G, seed=42, k=2)

for level, color in SEVERITY_COLORS.items():
    edges = [(u, v) for u, v, d in G.edges(data=True) if d.get("severity") == level]
    if edges:
        width = 4 if level == "major" else 2
        nx.draw_networkx_edges(G, pos, edgelist=edges, edge_color=color, width=width, alpha=0.8, ax=ax)

nx.draw_networkx_nodes(G, pos, node_color="#1565C0", node_size=1200, alpha=0.9, ax=ax)
nx.draw_networkx_labels(G, pos, font_color="white", font_size=8, font_weight="bold", ax=ax)

# Legend
from matplotlib.patches import Patch
legend = [Patch(color=c, label=l.capitalize()) for l, c in SEVERITY_COLORS.items()]
ax.legend(handles=legend, title="Severity", loc="upper right")
ax.set_title("Drug-Drug Interaction Network\n(DDInter)")
ax.axis("off")
plt.tight_layout()
plt.savefig("ddi_network.png", dpi=150, bbox_inches="tight")
print(f"Saved: ddi_network.png  ({G.number_of_nodes()} drugs, {G.number_of_edges()} interactions)")

import requests
import time
import pandas as pd

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

def find_drug_id(name):
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    res = r.json()["results"]
    return (res[0]["ddinter_id"], res[0]["drug_name"]) if res else (None, None)

def get_all_interactions(drug_id, page_size=200):
    all_results = []
    url = f"{BASE}/interaction/"
    params = {"drug_id": drug_id, "format": "json", "page_size": page_size}
    while url:
        r = requests.get(url, params=params, timeout=30)
        r.raise_for_status()
        data = r.json()
        all_results.extend(data.get("results", []))
        url = data.get("next")
        params = {}
    return all_results

# Build DDI profile for clopidogrel
drug_name = "clopidogrel"
drug_id, resolved_name = find_drug_id(drug_name)

if drug_id:
    print(f"Drug: {resolved_name} ({drug_id})")
    ixs = get_all_interactions(drug_id)
    df = pd.DataFrame(ixs)

    print(f"Total interactions: {len(df)}")
    if "level" in df.columns:
        print("\nSeverity breakdown:")
        for level, grp in df.groupby("level"):
            print(f"  {level:15s}: {len(grp):4d} interactions")

        # Major interactions table
        major = df[df["level"].str.lower() == "major"].copy()
        print(f"\nMajor interactions ({len(major)}):")
        for _, row in major.head(10).iterrows():
            partner = row.get("drug_b") if row.get("drug_a") == resolved_name else row.get("drug_a")
            mech = str(row.get("mechanism", ""))[:80]
            print(f"  + {partner}: {mech}")

    df.to_csv(f"{drug_name}_ddi_profile.csv", index=False)
    print(f"\nSaved: {drug_name}_ddi_profile.csv")

import requests
import time
import itertools
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

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

SEVERITY_SCORE = {"major": 3, "moderate": 2, "minor": 1, "none": 0}

def find_drug_id(name):
    r = requests.get(f"{BASE}/drug/",
                     params={"drug_name": name, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    res = r.json()["results"]
    return (res[0]["ddinter_id"], res[0]["drug_name"]) if res else (None, None)

def check_pair(id1, id2):
    r = requests.get(f"{BASE}/between/",
                     params={"drug1": id1, "drug2": id2, "format": "json"},
                     timeout=15)
    r.raise_for_status()
    return r.json().get("results", [])

# Drug panel
drug_names = ["warfarin", "aspirin", "atorvastatin", "fluconazole", "metformin"]
id_map = {}
for name in drug_names:
    ddid, rname = find_drug_id(name)
    if ddid:
        id_map[name] = (ddid, rname)
    time.sleep(0.3)

resolved = {name: rname for name, (ddid, rname) in id_map.items()}
n = len(id_map)
names = list(id_map.keys())
rnames = [resolved[n] for n in names]

# Build matrix
matrix = np.zeros((n, n), dtype=int)
for i, (n1, (id1, _)) in enumerate(id_map.items()):
    for j, (n2, (id2, _)) in enumerate(id_map.items()):
        if i < j:
            ixs = check_pair(id1, id2)
            if ixs:
                worst = max(SEVERITY_SCORE.get(ix.get("level", "none").lower(), 0) for ix in ixs)
                matrix[i, j] = matrix[j, i] = worst
            time.sleep(0.3)

# Heatmap
fig, ax = plt.subplots(figsize=(7, 6))
im = ax.imshow(matrix, cmap="RdYlGn_r", vmin=0, vmax=3)
ax.set_xticks(range(n))
ax.set_yticks(range(n))
ax.set_xticklabels(rnames, rotation=30, ha="right", fontsize=9)
ax.set_yticklabels(rnames, fontsize=9)
for i in range(n):
    for j in range(n):
        text = ["None", "Minor", "Mod", "Major"][matrix[i, j]]
        ax.text(j, i, text, ha="center", va="center", fontsize=7)
plt.colorbar(im, ax=ax, label="Severity (0=None, 3=Major)")
ax.set_title("Drug-Drug Interaction Severity Matrix\n(DDInter)")
plt.tight_layout()
plt.savefig("ddi_severity_matrix.png", dpi=150, bbox_inches="tight")
print("Saved: ddi_severity_matrix.png")