FDA Database Access
Overview
Access comprehensive FDA regulatory data through openFDA, the FDA's initiative to provide open APIs for public datasets. Query information about drugs, medical devices, foods, animal/veterinary products, and substances using Python with standardized interfaces.
Key capabilities:
- Query adverse events for drugs, devices, foods, and veterinary products
- Access product labeling, approvals, and regulatory submissions
- Monitor recalls and enforcement actions
- Look up National Drug Codes (NDC) and substance identifiers (UNII)
- Analyze device classifications and clearances (510k, PMA)
- Track drug shortages and supply issues
- Research chemical structures and substance relationships
When to Use This Skill
This skill should be used when working with:
- Drug research: Safety profiles, adverse events, labeling, approvals, shortages
- Medical device surveillance: Adverse events, recalls, 510(k) clearances, PMA approvals
- Food safety: Recalls, allergen tracking, adverse events, dietary supplements
- Veterinary medicine: Animal drug adverse events by species and breed
- Chemical/substance data: UNII lookup, CAS number mapping, molecular structures
- Regulatory analysis: Approval pathways, enforcement actions, compliance tracking
- Pharmacovigilance: Post-market surveillance, safety signal detection
- Scientific research: Drug interactions, comparative safety, epidemiological studies
Quick Start
1. Basic Setup
from scripts.fda_query import FDAQuery
# Initialize (API key optional but recommended)
fda = FDAQuery(api_key="YOUR_API_KEY")
# Query drug adverse events
events = fda.query_drug_events("aspirin", limit=100)
# Get drug labeling
label = fda.query_drug_label("Lipitor", brand=True)
# Search device recalls
recalls = fda.query("device", "enforcement",
search="classification:Class+I",
limit=50)
2. API Key Setup
While the API works without a key, registering provides higher rate limits:
- Without key: 240 requests/min, 1,000/day
- With key: 240 requests/min, 120,000/day
Register at: https://open.fda.gov/apis/authentication/
Set as environment variable:
export FDA_API_KEY="your_key_here"
3. Running Examples
# Run comprehensive examples
python scripts/fda_examples.py
# This demonstrates:
# - Drug safety profiles
# - Device surveillance
# - Food recall monitoring
# - Substance lookup
# - Comparative drug analysis
# - Veterinary drug analysis
FDA Database Categories
Drugs
Access 6 drug-related endpoints covering the full drug lifecycle from approval to post-market surveillance.
Endpoints:
- Adverse Events - Reports of side effects, errors, and therapeutic failures
- Product Labeling - Prescribing information, warnings, indications
- NDC Directory - National Drug Code product information
- Enforcement Reports - Drug recalls and safety actions
- Drugs@FDA - Historical approval data since 1939
- Drug Shortages - Current and resolved supply issues
Common use cases:
# Safety signal detection
fda.count_by_field("drug", "event",
search="patient.drug.medicinalproduct:metformin",
field="patient.reaction.reactionmeddrapt")
# Get prescribing information
label = fda.query_drug_label("Keytruda", brand=True)
# Check for recalls
recalls = fda.query_drug_recalls(drug_name="metformin")
# Monitor shortages
shortages = fda.query("drug", "drugshortages",
search="status:Currently+in+Shortage")
Reference: See references/drugs.md for detailed documentation
Devices
Access 9 device-related endpoints covering medical device safety, approvals, and registrations.
Endpoints:
- Adverse Events - Device malfunctions, injuries, deaths
- 510(k) Clearances - Premarket notifications
- Classification - Device categories and risk classes
- Enforcement Reports - Device recalls
- Recalls - Detailed recall information
- PMA - Premarket approval data for Class III devices
- Registrations & Listings - Manufacturing facility data
- UDI - Unique Device Identification database
- COVID-19 Serology - Antibody test performance data
Common use cases:
# Monitor device safety
events = fda.query_device_events("pacemaker", limit=100)
# Look up device classification
classification = fda.query_device_classification("DQY")
# Find 510(k) clearances
clearances = fda.query_device_510k(applicant="Medtronic")
# Search by UDI
device_info = fda.query("device", "udi",
search="identifiers.id:00884838003019")
Reference: See references/devices.md for detailed documentation
Foods
Access 2 food-related endpoints for safety monitoring and recalls.
Endpoints:
- Adverse Events - Food, dietary supplement, and cosmetic events
- Enforcement Reports - Food product recalls
Common use cases:
# Monitor allergen recalls
recalls = fda.query_food_recalls(reason="undeclared peanut")
# Track dietary supplement events
events = fda.query_food_events(
industry="Dietary Supplements")
# Find contamination recalls
listeria = fda.query_food_recalls(
reason="listeria",
classification="I")
Reference: See references/foods.md for detailed documentation
Animal & Veterinary
Access veterinary drug adverse event data with species-specific information.
Endpoint:
- Adverse Events - Animal drug side effects by species, breed, and product
Common use cases:
# Species-specific events
dog_events = fda.query_animal_events(
species="Dog",
drug_name="flea collar")
# Breed predisposition analysis
breed_query = fda.query("animalandveterinary", "event",
search="reaction.veddra_term_name:*seizure*+AND+"
"animal.breed.breed_component:*Labrador*")
Reference: See references/animal_veterinary.md for detailed documentation
Substances & Other
Access molecular-level substance data with UNII codes, chemical structures, and relationships.
Endpoints:
- Substance Data - UNII, CAS, chemical structures, relationships
- NSDE - Historical substance data (legacy)
Common use cases:
# UNII to CAS mapping
substance = fda.query_substance_by_unii("R16CO5Y76E")
# Search by name
results = fda.query_substance_by_name("acetaminophen")
# Get chemical structure
structure = fda.query("other", "substance",
search="names.name:ibuprofen+AND+substanceClass:chemical")
Reference: See references/other.md for detailed documentation
Common Query Patterns
Pattern 1: Safety Profile Analysis
Create comprehensive safety profiles combining multiple data sources:
def drug_safety_profile(fda, drug_name):
"""Generate complete safety profile."""
# 1. Total adverse events
events = fda.query_drug_events(drug_name, limit=1)
total = events["meta"]["results"]["total"]
# 2. Most common reactions
reactions = fda.count_by_field(
"drug", "event",
search=f"patient.drug.medicinalproduct:*{drug_name}*",
field="patient.reaction.reactionmeddrapt",
exact=True
)
# 3. Serious events
serious = fda.query("drug", "event",
search=f"patient.drug.medicinalproduct:*{drug_name}*+AND+serious:1",
limit=1)
# 4. Recent recalls
recalls = fda.query_drug_recalls(drug_name=drug_name)
return {
"total_events": total,
"top_reactions": reactions["results"][:10],
"serious_events": serious["meta"]["results"]["total"],
"recalls": recalls["results"]
}
Pattern 2: Temporal Trend Analysis
Analyze trends over time using date ranges:
from datetime import datetime, timedelta
def get_monthly_trends(fda, drug_name, months=12):
"""Get monthly adverse event trends."""
trends = []
f