Amendment Patterns Endpoint

Retrieve historical protocol amendment patterns by therapeutic area.

GET /patterns/{therapeutic_area}

Get statistical analysis of protocol amendments for a specific therapeutic area.

Request

GET /v1/patterns/Oncology
Authorization: Bearer YOUR_API_KEY

Path Parameters

Parameter	Type	Required	Description
therapeutic_area	string	Yes	Therapeutic area to analyze

Query Parameters

Parameter	Type	Default	Description
time_period	string	5_years	Analysis time period: 1_year, 3_years, 5_years, 10_years
phase	string	all	Filter by clinical phase: I, II, III, IV
include_details	boolean	false	Include detailed amendment examples

Therapeutic Areas

• Oncology
• Cardiovascular
• Neurology
• Psychiatry
• Immunology
• Rheumatology
• Infectious_Disease
• Rare_Disease

Response

{
  "therapeutic_area": "Oncology",
  "analysis_period": {
    "start": "2020-01-01",
    "end": "2024-12-31"
  },
  "total_trials_analyzed": 1247,
  "amendment_rate": 68.5,
  "patterns": [
    {
      "pattern_id": "PAT-001",
      "pattern_type": "endpoint_modification",
      "description": "Changes to primary or secondary endpoint definitions",
      "frequency": 32.4,
      "risk_level": "high",
      "avg_delay_months": 4.2,
      "common_triggers": [
        "Competitive landscape changes",
        "Regulatory feedback",
        "Interim analysis results"
      ],
      "prevention_strategies": [
        "Early FDA Type B meeting",
        "Comprehensive endpoint sensitivity analysis",
        "Adaptive design consideration"
      ]
    },
    {
      "pattern_id": "PAT-002",
      "pattern_type": "sample_size_increase",
      "description": "Increases to planned sample size",
      "frequency": 28.1,
      "risk_level": "medium",
      "avg_delay_months": 6.8,
      "common_triggers": [
        "Lower than expected effect size",
        "Higher dropout rate",
        "Subgroup analysis requirements"
      ],
      "prevention_strategies": [
        "Conservative effect size assumptions",
        "Dropout rate margins in power calculations",
        "Adaptive sample size re-estimation"
      ]
    }
  ],
  "phase_breakdown": {
    "I": { "amendment_rate": 45.2, "trial_count": 312 },
    "II": { "amendment_rate": 62.8, "trial_count": 456 },
    "III": { "amendment_rate": 78.4, "trial_count": 389 },
    "IV": { "amendment_rate": 52.1, "trial_count": 90 }
  },
  "query_metadata": {
    "processing_time_ms": 156,
    "query_id": "qry_pat_xyz",
    "data_sources": ["Clinical Trial Registry", "FDA Submission Database"]
  }
}

Response Fields

Field	Type	Description	Tier
therapeutic_area	string	Queried therapeutic area	All
analysis_period	object	Date range of analysis	All
total_trials_analyzed	number	Number of trials in dataset	All
amendment_rate	number	Overall amendment rate (%)	All
patterns	array	Identified amendment patterns	All
patterns[].frequency	number	Occurrence frequency (%)	All
patterns[].risk_level	string	Risk classification	All
patterns[].prevention_strategies	array	Prevention recommendations	Starter
phase_breakdown	object	Phase-specific statistics	Starter

Examples

Basic Request

curl -X GET "https://api.ctwise.ai/v1/patterns/Oncology" \
  -H "Authorization: Bearer ctwise_sk_live_xxx"

With Time Period

curl -X GET "https://api.ctwise.ai/v1/patterns/Cardiovascular?time_period=3_years" \
  -H "Authorization: Bearer ctwise_sk_live_xxx"

Phase-Specific Analysis

curl -X GET "https://api.ctwise.ai/v1/patterns/Oncology?phase=III&include_details=true" \
  -H "Authorization: Bearer ctwise_sk_live_xxx"

Python Example

import requests

API_KEY = "ctwise_sk_live_xxx"
BASE_URL = "https://api.ctwise.ai/v1"

response = requests.get(
    f"{BASE_URL}/patterns/Oncology",
    headers={"Authorization": f"Bearer {API_KEY}"},
    params={
        "time_period": "5_years",
        "phase": "III"
    }
)

data = response.json()
print(f"Amendment rate: {data['amendment_rate']}%")
print(f"Trials analyzed: {data['total_trials_analyzed']}")

for pattern in data['patterns']:
    print(f"\n{pattern['pattern_type']}:")
    print(f"  Frequency: {pattern['frequency']}%")
    print(f"  Risk Level: {pattern['risk_level']}")
    print(f"  Avg Delay: {pattern['avg_delay_months']} months")

Error Responses

Invalid Therapeutic Area

{
  "error": {
    "code": "INVALID_THERAPEUTIC_AREA",
    "message": "Therapeutic area 'InvalidArea' is not recognized."
  }
}

Status: 400 Bad Request

Insufficient Data

{
  "error": {
    "code": "INSUFFICIENT_DATA",
    "message": "Not enough trial data available for the specified criteria."
  }
}

Status: 404 Not Found

Tier Differences

Feature	Free	Starter
Basic patterns	✅ (top 3)	✅ (all)
Prevention strategies	❌	✅
Phase breakdown	❌	✅
Custom time periods	❌	✅
Detailed examples	❌	✅

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Related Endpoints

• POST /requirements/search - Search regulatory requirements
• POST /rules/validate - Protocol validation