#!/usr/bin/env python3"""FDA API Usage Examples Demonstrates common use cases for querying FDA databases. Usage: python fda_examples.py""" import osfrom fda_query import FDAQuery def example_drug_safety_profile(fda, drug_name): """ Create a comprehensive safety profile for a drug. Includes: - Total adverse events - Most common reactions - Serious events - Recent recalls """ print(f"\n{'='*60}") print(f"DRUG SAFETY PROFILE: {drug_name}") print(f"{'='*60}\n") # 1. Count total adverse events events = fda.query_drug_events(drug_name, limit=1) if "meta" in events and "results" in events["meta"]: total = events["meta"]["results"].get("total", 0) print(f"Total Adverse Event Reports: {total:,}") # 2. Most common reactions print(f"\nMost Common Adverse Reactions:") reactions = fda.count_by_field( "drug", "event", search=f"patient.drug.medicinalproduct:*{drug_name}*", field="patient.reaction.reactionmeddrapt", exact=True ) if "results" in reactions: for i, item in enumerate(reactions["results"][:10], 1): print(f" {i}. {item['term']}: {item['count']:,} reports") # 3. Serious events serious_events = fda.query( "drug", "event", search=f"patient.drug.medicinalproduct:*{drug_name}*+AND+serious:1", limit=1 ) if "meta" in serious_events and "results" in serious_events["meta"]: serious_total = serious_events["meta"]["results"].get("total", 0) print(f"\nSerious Adverse Events: {serious_total:,}") # 4. Check for recent recalls recalls = fda.query_drug_recalls(drug_name=drug_name) if "results" in recalls and len(recalls["results"]) > 0: print(f"\nRecent Recalls: {len(recalls['results'])}") for recall in recalls["results"][:3]: print(f" - {recall.get('reason_for_recall', 'Unknown')} " f"(Class {recall.get('classification', 'Unknown')})") else: print(f"\nRecent Recalls: None found") def example_device_surveillance(fda, device_name): """ Monitor medical device safety. Includes: - Adverse events - Event types (death, injury, malfunction) - Recent recalls """ print(f"\n{'='*60}") print(f"DEVICE SURVEILLANCE: {device_name}") print(f"{'='*60}\n") # 1. Count adverse events events = fda.query_device_events(device_name, limit=1) if "meta" in events and "results" in events["meta"]: total = events["meta"]["results"].get("total", 0) print(f"Total Adverse Event Reports: {total:,}") # 2. Event types print(f"\nEvent Type Distribution:") event_types = fda.count_by_field( "device", "event", search=f"device.brand_name:*{device_name}*", field="event_type", exact=False ) if "results" in event_types: for item in event_types["results"]: print(f" {item['term']}: {item['count']:,}") # 3. Recent events recent = fda.query_device_events(device_name, limit=5) if "results" in recent and len(recent["results"]) > 0: print(f"\nRecent Events (sample):") for i, event in enumerate(recent["results"][:3], 1): event_type = event.get("event_type", "Unknown") date = event.get("date_received", "Unknown") print(f" {i}. Type: {event_type}, Date: {date}") def example_food_recall_monitoring(fda, allergen): """ Monitor food recalls for specific allergen. Args: fda: FDAQuery instance allergen: Allergen to monitor (e.g., "peanut", "milk", "soy") """ print(f"\n{'='*60}") print(f"ALLERGEN RECALL MONITORING: {allergen}") print(f"{'='*60}\n") # Find recalls mentioning this allergen recalls = fda.query_food_recalls(reason=allergen) if "results" in recalls and len(recalls["results"]) > 0: print(f"Found {len(recalls['results'])} recalls mentioning '{allergen}':\n") for recall in recalls["results"][:10]: product = recall.get("product_description", "Unknown product") classification = recall.get("classification", "Unknown") reason = recall.get("reason_for_recall", "Unknown") date = recall.get("recall_initiation_date", "Unknown") status = recall.get("status", "Unknown") print(f"Product: {product}") print(f" Classification: {classification}") print(f" Reason: {reason}") print(f" Date: {date}") print(f" Status: {status}") print() else: print(f"No recent recalls found for allergen: {allergen}") def example_substance_lookup(fda, substance_name): """ Look up substance information. Includes: - UNII code - CAS numbers - Chemical structure - Related substances """ print(f"\n{'='*60}") print(f"SUBSTANCE INFORMATION: {substance_name}") print(f"{'='*60}\n") substances = fda.query_substance_by_name(substance_name) if "results" in substances and len(substances["results"]) > 0: for i, substance in enumerate(substances["results"][:3], 1): print(f"Match {i}:") # Names names = substance.get("names", []) if names: preferred = next((n["name"] for n in names if n.get("preferred")), names[0].get("name")) print(f" Name: {preferred}") # UNII unii = substance.get("approvalID") if unii: print(f" UNII: {unii}") # CAS numbers codes = substance.get("codes", []) cas_numbers = [c["code"] for c in codes if "CAS" in c.get("codeSystem", "")] if cas_numbers: print(f" CAS: {', '.join(cas_numbers)}") # Structure if "structure" in substance: structure = substance["structure"] formula = structure.get("formula") mol_weight = structure.get("molecularWeight") if formula: print(f" Formula: {formula}") if mol_weight: print(f" Molecular Weight: {mol_weight}") # Substance class substance_class = substance.get("substanceClass") if substance_class: print(f" Class: {substance_class}") print() else: print(f"No substances found matching: {substance_name}") def example_comparative_drug_analysis(fda, drug_list): """ Compare safety profiles of multiple drugs. Args: fda: FDAQuery instance drug_list: List of drug names to compare """ print(f"\n{'='*60}") print(f"COMPARATIVE DRUG ANALYSIS") print(f"{'='*60}\n") print(f"Comparing: {', '.join(drug_list)}\n") comparison = {} for drug in drug_list: # Get total events events = fda.query_drug_events(drug, limit=1) total = 0 if "meta" in events and "results" in events["meta"]: total = events["meta"]["results"].get("total", 0) # Get serious events serious = fda.query( "drug", "event", search=f"patient.drug.medicinalproduct:*{drug}*+AND+serious:1", limit=1 ) serious_total = 0 if "meta" in serious and "results" in serious["meta"]: serious_total = serious["meta"]["results"].get("total", 0) serious_rate = (serious_total / total * 100) if total > 0 else 0 comparison[drug] = { "total_events": total, "serious_events": serious_total, "serious_rate": serious_rate } # Display comparison print(f"{'Drug':<20} {'Total Events':>15} {'Serious Events':>15} {'Serious %':>12}") print("-" * 65) for drug, data in comparison.items(): print(f"{drug:<20} {data['total_events']:>15,} " f"{data['serious_events']:>15,} {data['serious_rate']:>11.2f}%") def example_veterinary_analysis(fda, species, drug_name): """ Analyze veterinary drug adverse events by species. Args: fda: FDAQuery instance species: Animal species (e.g., "Dog", "Cat", "Horse") drug_name: Veterinary drug name """ print(f"\n{'='*60}") print(f"VETERINARY DRUG ANALYSIS: {drug_name} in {species}") print(f"{'='*60}\n") events = fda.query_animal_events(species=species, drug_name=drug_name) if "results" in events and len(events["results"]) > 0: print(f"Found {len(events['results'])} adverse event reports\n") # Collect reactions reactions = [] serious_count = 0 for event in events["results"]: if event.get("serious_ae") == "true": serious_count += 1 if "reaction" in event: for reaction in event["reaction"]: if "veddra_term_name" in reaction: reactions.append(reaction["veddra_term_name"]) print(f"Serious Events: {serious_count} ({serious_count/len(events['results'])*100:.1f}%)") # Count reactions from collections import Counter reaction_counts = Counter(reactions) print(f"\nMost Common Reactions:") for reaction, count in reaction_counts.most_common(10): print(f" {reaction}: {count}") else: print(f"No adverse events found") def main(): """Run example analyses.""" # Get API key from environment api_key = os.environ.get("FDA_API_KEY") if not api_key: print("Warning: No FDA_API_KEY found in environment.") print("You can still use the API but with lower rate limits.") print("Set FDA_API_KEY environment variable for better performance.\n") # Initialize FDA query client fda = FDAQuery(api_key=api_key) # Run examples try: # Example 1: Drug safety profile example_drug_safety_profile(fda, "aspirin") # Example 2: Device surveillance example_device_surveillance(fda, "pacemaker") # Example 3: Food recall monitoring example_food_recall_monitoring(fda, "undeclared peanut") # Example 4: Substance lookup example_substance_lookup(fda, "ibuprofen") # Example 5: Comparative analysis example_comparative_drug_analysis(fda, ["aspirin", "ibuprofen", "naproxen"]) # Example 6: Veterinary analysis example_veterinary_analysis(fda, "Dog", "flea collar") except Exception as e: print(f"\nError running examples: {e}") print("This may be due to API rate limits or connectivity issues.") if __name__ == "__main__": main()
#!/usr/bin/env python3
"""
FDA API Usage Examples
Demonstrates common use cases for querying FDA databases.
Usage:
python fda_examples.py
"""
import os
from fda_query import FDAQuery
def example_drug_safety_profile(fda, drug_name):
"""
Create a comprehensive safety profile for a drug.
Includes:
- Total adverse events
- Most common reactions
- Serious events
- Recent recalls
"""
print(f"\n{'='*60}")
print(f"DRUG SAFETY PROFILE: {drug_name}")
print(f"{'='*60}\n")
# 1. Count total adverse events
events = fda.query_drug_events(drug_name, limit=1)
if "meta" in events and "results" in events["meta"]:
total = events["meta"]["results"].get("total", 0)
print(f"Total Adverse Event Reports: {total:,}")
# 2. Most common reactions
print(f"\nMost Common Adverse Reactions:")
reactions = fda.count_by_field(
"drug", "event",
search=f"patient.drug.medicinalproduct:*{drug_name}*",
field="patient.reaction.reactionmeddrapt",
exact=True
)
if "results" in reactions:
for i, item in enumerate(reactions["results"][:10], 1):
print(f" {i}. {item['term']}: {item['count']:,} reports")
# 3. Serious events
serious_events = fda.query(
"drug", "event",
search=f"patient.drug.medicinalproduct:*{drug_name}*+AND+serious:1",
limit=1
)
if "meta" in serious_events and "results" in serious_events["meta"]:
serious_total = serious_events["meta"]["results"].get("total", 0)
print(f"\nSerious Adverse Events: {serious_total:,}")
# 4. Check for recent recalls
recalls = fda.query_drug_recalls(drug_name=drug_name)
if "results" in recalls and len(recalls["results"]) > 0:
print(f"\nRecent Recalls: {len(recalls['results'])}")
for recall in recalls["results"][:3]:
print(f" - {recall.get('reason_for_recall', 'Unknown')} "
f"(Class {recall.get('classification', 'Unknown')})")
else:
print(f"\nRecent Recalls: None found")
def example_device_surveillance(fda, device_name):
"""
Monitor medical device safety.
Includes:
- Adverse events
- Event types (death, injury, malfunction)
- Recent recalls
"""
print(f"\n{'='*60}")
print(f"DEVICE SURVEILLANCE: {device_name}")
print(f"{'='*60}\n")
# 1. Count adverse events
events = fda.query_device_events(device_name, limit=1)
if "meta" in events and "results" in events["meta"]:
total = events["meta"]["results"].get("total", 0)
print(f"Total Adverse Event Reports: {total:,}")
# 2. Event types
print(f"\nEvent Type Distribution:")
event_types = fda.count_by_field(
"device", "event",
search=f"device.brand_name:*{device_name}*",
field="event_type",
exact=False
)
if "results" in event_types:
for item in event_types["results"]:
print(f" {item['term']}: {item['count']:,}")
# 3. Recent events
recent = fda.query_device_events(device_name, limit=5)
if "results" in recent and len(recent["results"]) > 0:
print(f"\nRecent Events (sample):")
for i, event in enumerate(recent["results"][:3], 1):
event_type = event.get("event_type", "Unknown")
date = event.get("date_received", "Unknown")
print(f" {i}. Type: {event_type}, Date: {date}")
def example_food_recall_monitoring(fda, allergen):
"""
Monitor food recalls for specific allergen.
Args:
fda: FDAQuery instance
allergen: Allergen to monitor (e.g., "peanut", "milk", "soy")
"""
print(f"\n{'='*60}")
print(f"ALLERGEN RECALL MONITORING: {allergen}")
print(f"{'='*60}\n")
# Find recalls mentioning this allergen
recalls = fda.query_food_recalls(reason=allergen)
if "results" in recalls and len(recalls["results"]) > 0:
print(f"Found {len(recalls['results'])} recalls mentioning '{allergen}':\n")
for recall in recalls["results"][:10]:
product = recall.get("product_description", "Unknown product")
classification = recall.get("classification", "Unknown")
reason = recall.get("reason_for_recall", "Unknown")
date = recall.get("recall_initiation_date", "Unknown")
status = recall.get("status", "Unknown")
print(f"Product: {product}")
print(f" Classification: {classification}")
print(f" Reason: {reason}")
print(f" Date: {date}")
print(f" Status: {status}")
print()
else:
print(f"No recent recalls found for allergen: {allergen}")
def example_substance_lookup(fda, substance_name):
"""
Look up substance information.
Includes:
- UNII code
- CAS numbers
- Chemical structure
- Related substances
"""
print(f"\n{'='*60}")
print(f"SUBSTANCE INFORMATION: {substance_name}")
print(f"{'='*60}\n")
substances = fda.query_substance_by_name(substance_name)
if "results" in substances and len(substances["results"]) > 0:
for i, substance in enumerate(substances["results"][:3], 1):
print(f"Match {i}:")
# Names
names = substance.get("names", [])
if names:
preferred = next((n["name"] for n in names if n.get("preferred")), names[0].get("name"))
print(f" Name: {preferred}")
# UNII
unii = substance.get("approvalID")
if unii:
print(f" UNII: {unii}")
# CAS numbers
codes = substance.get("codes", [])
cas_numbers = [c["code"] for c in codes if "CAS" in c.get("codeSystem", "")]
if cas_numbers:
print(f" CAS: {', '.join(cas_numbers)}")
# Structure
if "structure" in substance:
structure = substance["structure"]
formula = structure.get("formula")
mol_weight = structure.get("molecularWeight")
if formula:
print(f" Formula: {formula}")
if mol_weight:
print(f" Molecular Weight: {mol_weight}")
# Substance class
substance_class = substance.get("substanceClass")
if substance_class:
print(f" Class: {substance_class}")
print()
else:
print(f"No substances found matching: {substance_name}")
def example_comparative_drug_analysis(fda, drug_list):
"""
Compare safety profiles of multiple drugs.
Args:
fda: FDAQuery instance
drug_list: List of drug names to compare
"""
print(f"\n{'='*60}")
print(f"COMPARATIVE DRUG ANALYSIS")
print(f"{'='*60}\n")
print(f"Comparing: {', '.join(drug_list)}\n")
comparison = {}
for drug in drug_list:
# Get total events
events = fda.query_drug_events(drug, limit=1)
total = 0
if "meta" in events and "results" in events["meta"]:
total = events["meta"]["results"].get("total", 0)
# Get serious events
serious = fda.query(
"drug", "event",
search=f"patient.drug.medicinalproduct:*{drug}*+AND+serious:1",
limit=1
)
serious_total = 0
if "meta" in serious and "results" in serious["meta"]:
serious_total = serious["meta"]["results"].get("total", 0)
serious_rate = (serious_total / total * 100) if total > 0 else 0
comparison[drug] = {
"total_events": total,
"serious_events": serious_total,
"serious_rate": serious_rate
}
# Display comparison
print(f"{'Drug':<20} {'Total Events':>15} {'Serious Events':>15} {'Serious %':>12}")
print("-" * 65)
for drug, data in comparison.items():
print(f"{drug:<20} {data['total_events']:>15,} "
f"{data['serious_events']:>15,} {data['serious_rate']:>11.2f}%")
def example_veterinary_analysis(fda, species, drug_name):
"""
Analyze veterinary drug adverse events by species.
Args:
fda: FDAQuery instance
species: Animal species (e.g., "Dog", "Cat", "Horse")
drug_name: Veterinary drug name
"""
print(f"\n{'='*60}")
print(f"VETERINARY DRUG ANALYSIS: {drug_name} in {species}")
print(f"{'='*60}\n")
events = fda.query_animal_events(species=species, drug_name=drug_name)
if "results" in events and len(events["results"]) > 0:
print(f"Found {len(events['results'])} adverse event reports\n")
# Collect reactions
reactions = []
serious_count = 0
for event in events["results"]:
if event.get("serious_ae") == "true":
serious_count += 1
if "reaction" in event:
for reaction in event["reaction"]:
if "veddra_term_name" in reaction:
reactions.append(reaction["veddra_term_name"])
print(f"Serious Events: {serious_count} ({serious_count/len(events['results'])*100:.1f}%)")
# Count reactions
from collections import Counter
reaction_counts = Counter(reactions)
print(f"\nMost Common Reactions:")
for reaction, count in reaction_counts.most_common(10):
print(f" {reaction}: {count}")
else:
print(f"No adverse events found")
def main():
"""Run example analyses."""
# Get API key from environment
api_key = os.environ.get("FDA_API_KEY")
if not api_key:
print("Warning: No FDA_API_KEY found in environment.")
print("You can still use the API but with lower rate limits.")
print("Set FDA_API_KEY environment variable for better performance.\n")
# Initialize FDA query client
fda = FDAQuery(api_key=api_key)
# Run examples
try:
# Example 1: Drug safety profile
example_drug_safety_profile(fda, "aspirin")
# Example 2: Device surveillance
example_device_surveillance(fda, "pacemaker")
# Example 3: Food recall monitoring
example_food_recall_monitoring(fda, "undeclared peanut")
# Example 4: Substance lookup
example_substance_lookup(fda, "ibuprofen")
# Example 5: Comparative analysis
example_comparative_drug_analysis(fda, ["aspirin", "ibuprofen", "naproxen"])
# Example 6: Veterinary analysis
example_veterinary_analysis(fda, "Dog", "flea collar")
except Exception as e:
print(f"\nError running examples: {e}")
print("This may be due to API rate limits or connectivity issues.")
if __name__ == "__main__":
main()