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SKILL.md
ClinicalTrials.gov v2 API Guide
Overview
ClinicalTrials.gov is the world's largest clinical trial registry, maintained by the U.S. National Library of Medicine (NLM) at NIH. It contains over 576,000 study records from 220+ countries covering interventional trials, observational studies, and expanded access programs. The v2 API provides structured JSON access with field-level filtering, cursor-based pagination, and statistics endpoints.
Key v2 improvements over the legacy API: JSON-native responses, sparse field selection via the fields parameter, nextPageToken pagination, and dedicated statistics endpoints. Study data is organized into protocolSection (sponsor-submitted) and derivedSection (NLM-computed).
Authentication
No authentication required. All endpoints are publicly accessible without API keys or registration. Users should comply with NCBI usage policies and maintain reasonable request rates.
Core Endpoints
Search Studies
URL: GET https://clinicaltrials.gov/api/v2/studies
Parameters:
Parameter
Type
Required
Description
query.term
string
No
Free-text search across all fields
query.cond
string
No
Condition or disease filter
query.intr
string
No
Intervention or treatment filter
query.spons
string
No
Sponsor or collaborator filter
filter.overallStatus
string
No
RECRUITING, COMPLETED, , etc.
ACTIVE_NOT_RECRUITING
filter.phase
string
No
EARLY_PHASE1, PHASE1, PHASE2, PHASE3, PHASE4, NA
filter.geo
string
No
Geographic filter (distance(lat,lng,dist))
fields
string
No
Comma-separated fields for sparse response
sort
string
No
Sort field and direction (e.g., LastUpdatePostDate:desc)
No formal rate limits are published for the v2 API. Follow NCBI usage guidelines: stay under 3 requests/second without an API key, up to 10/second with one. For bulk data access, use the AACT relational database (https://aact.ctti-clinicaltrials.org/) or downloadable flat files rather than paginating through the full API.
Academic Use Cases
Systematic reviews: Use query.cond + query.intr + filter.overallStatus=COMPLETED to build PRISMA-compliant trial inventories. Paginate with nextPageToken to collect all records, then extract outcomes and enrollment for quantitative synthesis.
Landscape mapping: Combine search with stats/fieldValues to map phase distributions, sponsor concentration, and geographic spread for a therapeutic area -- useful for identifying evidence gaps in grant proposals.
Recruitment tracking: Filter by RECRUITING status and filter.geo to find active enrollment opportunities. Automate periodic queries for new trials in your domain.
Code Examples
Paginated Collection for Systematic Review
import requests, time
def collect_trials(condition, intervention, status="COMPLETED"):
base = "https://clinicaltrials.gov/api/v2/studies"
studies, token = [], None
while True:
params = {
"query.cond": condition, "query.intr": intervention,
"filter.overallStatus": status, "pageSize": 100,
"fields": "NCTId,BriefTitle,Phase,EnrollmentCount,CompletionDate",
}
if token:
params["pageToken"] = token
data = requests.get(base, params=params).json()
studies.extend(data.get("studies", []))
token = data.get("nextPageToken")
if not token:
break
time.sleep(0.34)
return studies
trials = collect_trials("type 2 diabetes", "metformin")
print(f"Collected {len(trials)} completed metformin T2D trials")
Sponsor and Phase Analysis
import requests
from collections import Counter
params = {"query.cond": "Alzheimer's Disease", "pageSize": 100,
"fields": "NCTId,Phase,LeadSponsorName"}
data = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params).json()
phases, sponsors = Counter(), Counter()
for s in data["studies"]:
p = s["protocolSection"]
for ph in p.get("designModule", {}).get("phases", []):
phases[ph] += 1
sponsors[p.get("sponsorCollaboratorsModule", {})
.get("leadSponsor", {}).get("name", "Unknown")] += 1
for ph, n in phases.most_common():
print(f"{ph}: {n}")
