ClinicalTrials.gov Database

Overview

ClinicalTrials.gov is a comprehensive registry of clinical studies conducted worldwide, maintained by the U.S. National Library of Medicine. Access API v2 to search for trials, retrieve detailed study information, filter by various criteria, and export data for analysis. The API is public (no authentication required) with rate limits of ~50 requests per minute, supporting JSON and CSV formats.

When to Use This Skill

This skill should be used when working with clinical trial data in scenarios such as:

• Patient matching - Finding recruiting trials for specific conditions or patient populations
• Research analysis - Analyzing clinical trial trends, outcomes, or study designs
• Drug/intervention research - Identifying trials testing specific drugs or interventions
• Geographic searches - Locating trials in specific locations or regions
• Sponsor/organization tracking - Finding trials conducted by specific institutions
• Data export - Extracting clinical trial data for further analysis or reporting
• Trial monitoring - Tracking status updates or results for specific trials
• Eligibility screening - Reviewing inclusion/exclusion criteria for trials

Quick Start

Basic Search Query

Search for clinical trials using the helper script:

cd scientific-databases/clinicaltrials-database/scripts
python3 query_clinicaltrials.py

Or use Python directly with the requests library:

import requests

url = "https://clinicaltrials.gov/api/v2/studies"
params = {
    "query.cond": "breast cancer",
    "filter.overallStatus": "RECRUITING",
    "pageSize": 10
}

response = requests.get(url, params=params)
data = response.json()

print(f"Found {data['totalCount']} trials")

Retrieve Specific Trial

Get detailed information about a trial using its NCT ID:

import requests

nct_id = "NCT04852770"
url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}"

response = requests.get(url)
study = response.json()

# Access specific modules
title = study['protocolSection']['identificationModule']['briefTitle']
status = study['protocolSection']['statusModule']['overallStatus']

Core Capabilities

1. Search by Condition/Disease

Find trials studying specific medical conditions or diseases using the query.cond parameter.

Example: Find recruiting diabetes trials

from scripts.query_clinicaltrials import search_studies

results = search_studies(
    condition="type 2 diabetes",
    status="RECRUITING",
    page_size=20,
    sort="LastUpdatePostDate:desc"
)

print(f"Found {results['totalCount']} recruiting diabetes trials")
for study in results['studies']:
    protocol = study['protocolSection']
    nct_id = protocol['identificationModule']['nctId']
    title = protocol['identificationModule']['briefTitle']
    print(f"{nct_id}: {title}")

Common use cases:

• Finding trials for rare diseases
• Identifying trials for comorbid conditions
• Tracking trial availability for specific diagnoses

2. Search by Intervention/Drug

Search for trials testing specific interventions, drugs, devices, or procedures using the query.intr parameter.

Example: Find Phase 3 trials testing Pembrolizumab

from scripts.query_clinicaltrials import search_studies

results = search_studies(
    intervention="Pembrolizumab",
    status=["RECRUITING", "ACTIVE_NOT_RECRUITING"],
    page_size=50
)

# Filter by phase in results
phase3_trials = [
    study for study in results['studies']
    if 'PHASE3' in study['protocolSection'].get('designModule', {}).get('phases', [])
]

Common use cases:

• Drug development tracking
• Competitive intelligence for pharmaceutical companies
• Treatment option research for clinicians

3. Geographic Search

Find trials in specific locations using the query.locn parameter.

Example: Find cancer trials in New York

from scripts.query_clinicaltrials import search_studies

results = search_studies(
    condition="cancer",
    location="New York",
    status="RECRUITING",
    page_size=100
)

# Extract location details
for study in results['studies']:
    locations_module = study['protocolSection'].get('contactsLocationsModule', {})
    locations = locations_module.get('locations', [])
    for loc in locations:
        if 'New York' in loc.get('city', ''):
            print(f"{loc['facility']}: {loc['city']}, {loc.get('state', '')}")

Common use cases:

• Patient referrals to local trials
• Geographic trial distribution analysis
• Site selection for new trials

4. Search by Sponsor/Organization

Find trials conducted by specific organizations using the query.spons parameter.

Example: Find trials sponsored by NCI

from scripts.query_clinicaltrials import search_studies

results = search_studies(
    sponsor="National Cancer Institute",
    page_size=100
)

# Extract sponsor information
for study in results['studies']:
    sponsor_module = study['protocolSection']['sponsorCollaboratorsModule']
    lead_sponsor = sponsor_module['leadSponsor']['name']
    collaborators = sponsor_module.get('collaborators', [])
    print(f"Lead: {lead_sponsor}")
    if collaborators:
        print(f"  Collaborators: {', '.join([c['name'] for c in collaborators])}")

Common use cases:

• Tracking institutional research portfolios
• Analyzing funding organization priorities
• Identifying collaboration opportunities

5. Filter by Study Status

Filter trials by recruitment or completion status using the filter.overallStatus parameter.

Valid status values:

• RECRUITING - Currently recruiting participants
• NOT_YET_RECRUITING - Not yet open for recruitment
• ENROLLING_BY_INVITATION - Only enrolling by invitation
• ACTIVE_NOT_RECRUITING - Active but no longer recruiting
• SUSPENDED - Temporarily halted
• TERMINATED - Stopped prematurely
• COMPLETED - Study has concluded
• WITHDRAWN - Withdrawn prior to enrollment

Example: Find recently completed trials with results

from scripts.query_clinicaltrials import search_studies

results = search_studies(
    condition="alzheimer disease",
    status="COMPLETED",
    sort="LastUpdatePostDate:desc"
how to use clinicaltrials-database
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use clinicaltrials-database on Cursor
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1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add clinicaltrials-database
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/davila7/claude-code-templates --skill clinicaltrials-databasecopy
The skills CLI fetches clinicaltrials-database from GitHub repository davila7/claude-code-templates and configures it for Cursor.
3
Select Cursor when prompted
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4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/clinicaltrials-database
Reload or restart Cursor to activate clinicaltrials-database. Access the skill through slash commands (e.g., /clinicaltrials-database) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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