/clinicaltrials-database-search

name: clinicaltrials-database-search
description: Query ClinicalTrials.gov API v2 for trial data. Search by condition, drug/intervention, location, sponsor, or phase; fetch details by NCT ID; filter by status; paginate; export CSV. For clinical research, patient matching, and trial portfolio analysis.
license: CC-BY-4.0

ClinicalTrials.gov Database — Clinical Trial Search

Overview

Query the ClinicalTrials.gov API v2 (public, no authentication) to search and retrieve clinical trial data worldwide. Supports searching by condition, intervention, location, sponsor, and status; retrieving detailed study information by NCT ID; paginating large result sets; and exporting to CSV.

When to Use

• Searching for recruiting clinical trials for a specific condition or disease
• Finding trials testing a specific drug, device, or intervention
• Locating trials in a specific geographic region for patient referral
• Tracking a sponsor's or institution's clinical trial portfolio
• Retrieving detailed eligibility criteria, outcomes, and contacts for a specific trial
• Analyzing clinical trial trends (phases, enrollment, timelines) across a therapeutic area
• Exporting trial data for systematic reviews or meta-analyses
• Monitoring trial status changes and results postings
• For chemical compound bioactivity data use chembl-database-bioactivity instead; for published literature use pubmed-database

Prerequisites

uv pip install requests pandas

**API details**:

• Base URL: `https://clinicaltrials.gov/api/v2`
• Authentication: None required (public API)
• Rate limit: ~50 requests/minute per IP
• Response formats: JSON (default), CSV
• Max page size: 1000 studies per request
• Date format: ISO 8601; text fields use CommonMark Markdown

Quick Start

import requests
import time

CT_API = "https://clinicaltrials.gov/api/v2"

def ct_search(params):
    """Reusable helper for ClinicalTrials.gov searches."""
    response = requests.get(f"{CT_API}/studies", params=params, timeout=30)
    response.raise_for_status()
    return response.json()

# Search for recruiting breast cancer trials
results = ct_search({
    "query.cond": "breast cancer",
    "filter.overallStatus": "RECRUITING",
    "pageSize": 10,
    "sort": "LastUpdatePostDate:desc"
})
print(f"Found {results['totalCount']} trials")
for study in results['studies'][:3]:
    nct = study['protocolSection']['identificationModule']['nctId']
    title = study['protocolSection']['identificationModule']['briefTitle']
    print(f"  {nct}: {title}")

Key Concepts

Response Data Structure

ClinicalTrials.gov returns deeply nested JSON. Key navigation paths:

| Data | Path | |------|------| | NCT ID | `study['protocolSection']['identificationModule']['nctId']` | | Title | `study['protocolSection']['identificationModule']['briefTitle']` | | Status | `study['protocolSection']['statusModule']['overallStatus']` | | Phase | `study['protocolSection']['designModule']['phases']` | | Enrollment | `study['protocolSection']['designModule']['enrollmentInfo']['count']` | | Eligibility | `study['protocolSection']['eligibilityModule']` | | Locations | `study['protocolSection']['contactsLocationsModule']['locations']` | | Interventions | `study['protocolSection']['armsInterventionsModule']['interventions']` | | Results | `study.get('resultsSection')` (None if no results posted) |

Study Status Values

| Status | Description | |--------|-------------| | `RECRUITING` | Currently recruiting participants | | `NOT_YET_RECRUITING` | Approved but not yet open | | `ENROLLING_BY_INVITATION` | Invitation-only enrollment | | `ACTIVE_NOT_RECRUITING` | Active, enrollment closed | | `SUSPENDED` | Temporarily halted | | `TERMINATED` | Stopped prematurely | | `COMPLETED` | Study concluded | | `WITHDRAWN` | Withdrawn before enrollment |

Study Phase Values

| Phase | Description | |-------|-------------| | `EARLY_PHASE1` | Early Phase 1 (formerly Phase 0) | | `PHASE1` | Phase 1 — safety and dosing | | `PHASE2` | Phase 2 — efficacy and side effects | | `PHASE3` | Phase 3 — large-scale efficacy | | `PHASE4` | Phase 4 — post-market surveillance | | `NA` | Not applicable (non-drug studies) |

Query Parameters Reference

| Parameter | Type | Description | Example | |-----------|------|-------------|---------| | `query.cond` | string | Condition/disease | `lung cancer` | | `query.intr` | string | Intervention/drug | `Pembrolizumab` | | `query.locn` | string | Geographic location | `New York` | | `query.spons` | string | Sponsor name | `National Cancer Institute` | | `query.term` | string | General full-text search | `immunotherapy` | | `filter.overallStatus` | string | Status filter (comma-separated) | `RECRUITING,COMPLETED` | | `filter.phase` | string | Phase filter | `PHASE2,PHASE3` | | `filter.ids` | string | NCT ID filter | `NCT04852770` | | `sort` | string | Sort order | `LastUpdatePostDate:desc` | | `pageSize` | int | Results per page (max 1000) | `100` | | `pageToken` | string | Pagination token | (from previous response) | | `format` | string | Response format | `json` or `csv` |

**Sort options**: `LastUpdatePostDate`, `EnrollmentCount`, `StartDate`, `StudyFirstPostDate` — each with `:asc` or `:desc`.

Core API

1. Search by Condition

results = ct_search({
    "query.cond": "type 2 diabetes",
    "filter.overallStatus": "RECRUITING",
    "pageSize": 20,
    "sort": "LastUpdatePostDate:desc"
})
print(f"Found {results['totalCount']} recruiting diabetes trials")
for study in results['studies'][:5]:
    proto = study['protocolSection']
    nct = proto['identificationModule']['nctId']
    title = proto['identificationModule']['briefTitle']
    print(f"  {nct}: {title}")

2. Search by Intervention/Drug

# Find Phase 3 trials testing Pembrolizumab
results = ct_search({
    "query.intr": "Pembrolizumab",
    "filter.overallStatus": "RECRUITING,ACTIVE_NOT_RECRUITING",
    "filter.phase": "PHASE3",
    "pag