fda-database - Agent Skills

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

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 = []
    for i in range(months):
        end = datetime.now() - timedelta(days=30i)
        start = end - timedelta(days=30)
        date_range = f"[{start.strftime('%Y%m%d')}+TO+{end.strftime('%Y%m%d')}]"
        search = f"patient.drug.medicinalproduct:{drug_name}+AND+receivedate:{date_range}"
        result = fda.query("drug", "event", search=search, limit=1)
        count = result["meta"]["results"]["total"] if "meta" in result else 0
        trends.append({
            "month": start.strftime("%Y-%m"),
            "events": count
        })    return trends

Pattern 3: Comparative Analysis

Compare multiple products side-by-side:

def compare_drugs(fda, drug_list):
    """Compare safety profiles of multiple drugs."""
    comparison = {}
    for drug in drug_list:
        # Total events
        events = fda.query_drug_events(drug, limit=1)
        total = events["meta"]["results"]["total"] if "meta" in events else 0        # Serious events
        serious = fda.query("drug", "event",
            search=f"patient.drug.medicinalproduct:{drug}+AND+serious:1",
            limit=1)
        serious_count = serious["meta"]["results"]["total"] if "meta" in serious else 0
        comparison[drug] = {
            "total_events": total,
            "serious_events": serious_count,
            "serious_rate": (serious_count/total100) if total > 0 else 0
        }    return comparison

Pattern 4: Cross-Database Lookup

Link data across multiple endpoints:

def comprehensive_device_lookup(fda, device_name):
    """Look up device across all relevant databases."""    return {
        "adverse_events": fda.query_device_events(device_name, limit=10),
        "510k_clearances": fda.query_device_510k(device_name=device_name),
        "recalls": fda.query("device", "enforcement",
                           search=f"product_description:{device_name}"),
        "udi_info": fda.query("device", "udi",
                            search=f"brand_name:{device_name}")
    }

Working with Results

Response Structure

All API responses follow this structure:

{
    "meta": {
        "disclaimer": "...",
        "results": {
            "skip": 0,
            "limit": 100,
            "total": 15234
        }
    },
    "results": [
        # Array of result objects
    ]
}

Error Handling

Always handle potential errors:

result = fda.query_drug_events("aspirin", limit=10)if "error" in result:
    print(f"Error: {result['error']}")
elif "results" not in result or len(result["results"]) == 0:
    print("No results found")
else:
    # Process results
    for event in result["results"]:
        # Handle event data
        pass

Pagination

For large result sets, use pagination:

# Automatic pagination
all_results = fda.query_all(
    "drug", "event",
    search="patient.drug.medicinalproduct:aspirin",
    max_results=5000
)
Manual pagination

for skip in range(0, 1000, 100):
    batch = fda.query("drug", "event",
                     search="...",
                     limit=100,
                     skip=skip)
    # Process batch

Best Practices

1. Use Specific Searches

DO:

# Specific field search
search="patient.drug.medicinalproduct:aspirin"

DON'T:

# Overly broad wildcard
search="aspirin"

2. Implement Rate Limiting

The FDAQuery class handles rate limiting automatically, but be aware of limits:

240 requests per minute

120,000 requests per day (with API key)

3. Cache Frequently Accessed Data

The FDAQuery class includes built-in caching (enabled by default):

# Caching is automatic
fda = FDAQuery(api_key=api_key, use_cache=True, cache_ttl=3600)

4. Use Exact Matching for Counting

When counting/aggregating, use .exact suffix:

# Count exact phrases
fda.count_by_field("drug", "event",
                  search="...",
                  field="patient.reaction.reactionmeddrapt",
                  exact=True)  # Adds .exact automatically

5. Validate Input Data

Clean and validate search terms:

def clean_drug_name(name):
    """Clean drug name for query."""
    return name.strip().replace('"', '\\"')drug_name = clean_drug_name(user_input)

API Reference

For detailed information about:

Authentication and rate limits → See references/api_basics.md

Drug databases → See references/drugs.md

Device databases → See references/devices.md

Food databases → See references/foods.md

Animal/veterinary databases → See references/animal_veterinary.md

Substance databases → See references/other.md

Scripts

`scripts/fda_query.py`

Main query module with FDAQuery class providing:

Unified interface to all FDA endpoints

Automatic rate limiting and caching

Error handling and retry logic

Common query patterns

`scripts/fda_examples.py`

Comprehensive examples demonstrating:

Drug safety profile analysis

Device surveillance monitoring

Food recall tracking

Substance lookup

Comparative drug analysis

Veterinary drug analysis

Run examples:

python scripts/fda_examples.py

Additional Resources

openFDA Homepage: https://open.fda.gov/

API Documentation: https://open.fda.gov/apis/

Interactive API Explorer: https://open.fda.gov/apis/try-the-api/

GitHub Repository: https://github.com/FDA/openfda

Terms of Service: https://open.fda.gov/terms/

Support and Troubleshooting

Common Issues

Issue: Rate limit exceeded

Solution: Use API key, implement delays, or reduce request frequency

Issue: No results found

Solution: Try broader search terms, check spelling, use wildcards

Issue: Invalid query syntax

Solution: Review query syntax in references/api_basics.md

Issue: Missing fields in results

Solution: Not all records contain all fields; always check field existence

Getting Help

GitHub Issues: https://github.com/FDA/openfda/issues

Email: open-fda@fda.hhs.gov

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