ClinicalTrials.gov Trial Sites Scraper

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Export ClinicalTrials.gov studies as one row per trial site or facility. This Apify Actor uses the official public ClinicalTrials.gov v2 API and returns clean, spreadsheet-ready rows for site selection, patient recruitment planning, competitive trial footprint analysis, and healthcare market research.

It is deliberately site-centric. Instead of giving you only one nested JSON record per clinical study, it expands each study's listed locations into separate dataset rows with trial context attached to every facility.

What does ClinicalTrials.gov Trial Sites Scraper do?

ClinicalTrials.gov Trial Sites Scraper searches public ClinicalTrials.gov records and flattens trial location data.

Each output row represents a facility/site and includes:

• 🧪 NCT ID, title, status, phase, sponsor, and study type
• 🏥 facility name, site status, city, state, ZIP, country, and coordinates when available
• 👤 site contact strings when ClinicalTrials.gov publishes them
• 📅 start, primary completion, completion, and last-update dates
• 📋 conditions, interventions, enrollment, eligibility, and summary fields
• 🔗 source URL back to the official ClinicalTrials.gov study page

Who is it for?

This actor is built for teams that need facility-level clinical trial intelligence:

• Pharma business development teams mapping competitor trial footprints
• CRO site-selection teams building investigator and facility shortlists
• Patient recruitment vendors planning geography-specific campaigns
• Biotech analysts tracking active studies by indication and sponsor
• Healthcare market researchers monitoring trial activity in target regions
• Data teams that need a repeatable API-to-dataset workflow on Apify

Why use this actor?

ClinicalTrials.gov records are rich, but the official JSON is nested by study. For commercial workflows, the unit of analysis is often the site.

This actor saves time by:

• converting nested API responses into flat rows
• preserving trial context on every location row
• supporting location, status, phase, sponsor, intervention, and NCT ID inputs
• producing a stable dataset schema for BI tools and enrichment pipelines
• avoiding browser automation because the official API is public

How is this different from generic clinical trial scrapers?

Most generic clinical trial scrapers focus on study-level records. That is useful for search, but less useful for site planning.

This actor is different because it is optimized for location intelligence:

• one row per trial site/facility
• coordinates when ClinicalTrials.gov provides them
• facility status and contacts where available
• easy grouping by country, state, city, sponsor, phase, or condition

Data you can extract

How much does it cost to scrape ClinicalTrials.gov trial sites?

The actor uses pay-per-event pricing:

• A small start event is charged once per run.
• A result event is charged for each trial-site row saved.

Current formula-derived pricing is $0.005 per run plus tiered per-site pricing. BRONZE is $0.000026842 per trial-site row, with lower prices on higher Apify tiers. Default examples are intentionally small so first runs are inexpensive, and Apify displays the maximum charge before you run the actor.

Input overview

You can search by:

• condition or disease
• intervention, drug, biologic, procedure, or device
• sponsor or collaborator
• recruitment status
• trial phase
• country, state, and city
• start date or last-update date ranges
• direct NCT IDs

Example input: recruiting diabetes sites in the United States

{
"condition":"diabetes",
"statuses":["RECRUITING","NOT_YET_RECRUITING"],
"country":"United States",
"maxItems":100
}

Example input: sponsor footprint

{
"condition":"oncology",
"sponsor":"AstraZeneca",
"statuses":["RECRUITING"],
"maxItems":250
}

Example input: known NCT IDs

{
"nctIds":["NCT03723486","NCT04280705"],
"maxItems":50,
"includeStudiesWithoutLocations":true
}

Output example

{
"nctId":"NCT03723486",
"sourceUrl":"https://clinicaltrials.gov/study/NCT03723486",
"briefTitle":"Bariatric Surgery: Microbiome & Diabetes",
"overallStatus":"UNKNOWN",
"phases":[],
"leadSponsor":"University Health Network, Toronto",
"facilityName":"University Health Network, Toronto General Hospital",
"city":"Toronto",
"state":"Ontario",
"country":"Canada",
"latitude":43.70643,
"longitude":-79.39864,
"conditions":["Obesity"],
"startDate":"2015-11",
"enrollmentCount":120
}

How to use it on Apify

1. Open the actor on Apify.
2. Enter a condition or a list of NCT IDs.
3. Add optional location, status, phase, sponsor, or date filters.
4. Set maxItems to the number of trial-site rows you need.
5. Run the actor.
6. Download the dataset as JSON, CSV, Excel, XML, or RSS.

Tips for better results

• Use broad condition terms first, then narrow by sponsor or geography.
• Leave phase empty if you want observational studies too.
• Use includeStudiesWithoutLocations only when study-level placeholder rows are acceptable.
• For national footprint mapping, filter by country but leave state and city empty.
• For competitive monitoring, use sponsor plus condition and repeat the same input weekly.

Integrations

Common integration patterns include:

• sending CSV exports to Airtable or Google Sheets
• loading JSON into Snowflake, BigQuery, or Postgres
• joining site rows with internal investigator CRM data
• mapping latitude/longitude fields in BI tools
• triggering weekly runs from Apify schedules
• feeding recruitment territory dashboards

API usage: Node.js

import{ ApifyClient }from'apify-client';
const client =newApifyClient({token: process.env.APIFY_TOKEN});
const run =await client.actor('automation-lab/clinicaltrials-trial-sites-scraper').call({
condition:'diabetes',
country:'United States',
statuses:['RECRUITING'],
maxItems:100,
});
console.log(run.defaultDatasetId);

API usage: Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('automation-lab/clinicaltrials-trial-sites-scraper').call(run_input={
'condition':'diabetes',
'country':'United States',
'statuses':['RECRUITING'],
'maxItems':100,
})
print(run['defaultDatasetId'])

API usage: cURL

curl-X POST 'https://api.apify.com/v2/acts/automation-lab~clinicaltrials-trial-sites-scraper/runs?token=YOUR_APIFY_TOKEN'\
-H'Content-Type: application/json'\
-d'{"condition":"diabetes","country":"United States","statuses":["RECRUITING"],"maxItems":100}'

MCP integration

Use this actor from AI tools through Apify MCP. The recommended HTTP endpoint is:

https://mcp.apify.com/?tools=automation-lab/clinicaltrials-trial-sites-scraper

Claude Code setup:

claude mcp add--transport http apify-clinicaltrials-sites \
"https://mcp.apify.com/?tools=automation-lab/clinicaltrials-trial-sites-scraper"\
--header"Authorization: Bearer YOUR_APIFY_TOKEN"

Claude Desktop / Cursor / VS Code HTTP configuration:

{
"mcpServers":{
"apify-clinicaltrials-sites":{
"type":"http",
"url":"https://mcp.apify.com/?tools=automation-lab/clinicaltrials-trial-sites-scraper",
"headers":{
"Authorization":"Bearer YOUR_APIFY_TOKEN"
}
}
}
}

If your MCP client only supports local stdio servers, use Apify's npm bridge:

$npx @apify/actors-mcp-server --actors automation-lab/clinicaltrials-trial-sites-scraper

Example prompts:

• "Find recruiting diabetes trial sites in California and summarize the sponsors."
• "Export oncology trial facilities for this sponsor and group them by country."
• "Compare active trial-site locations for two NCT ID lists."

Scheduling and monitoring

You can schedule the actor in Apify to monitor new or updated clinical trial sites.

Suggested schedules:

• weekly for competitor sponsor footprints
• monthly for broad indication maps
• daily for urgent recruitment campaigns

Use the same input over time so dataset counts and geography changes are comparable.

Data source

The actor uses the official public ClinicalTrials.gov v2 API at:

https://clinicaltrials.gov/api/v2/studies

No login, cookies, browser automation, or API key is required for the source data.

Limitations

• Contacts are only available when ClinicalTrials.gov publishes them.
• Some studies do not list facility-level locations.
• Location coordinates are not guaranteed for every facility.
• ClinicalTrials.gov data reflects submitted registry records and may lag real-world site changes.
• Date filters depend on the source API's supported search syntax.

Legality

ClinicalTrials.gov is a public registry. Use the exported data responsibly and comply with applicable laws, privacy rules, clinical research regulations, and Apify's Terms of Service. Do not use contact information for spam or unlawful outreach.

Legal and ethical use

The actor exports public registry records, not private patient data. Users remain responsible for their own compliance review before using site contacts, investigator information, or trial metadata in outreach, analytics, or regulated workflows.

FAQ

Does this actor scrape private patient data?

No. It exports public clinical trial registry records and facility/site metadata from ClinicalTrials.gov.

Why did I get fewer rows than expected?

Your filters may be narrow, or studies may not have listed facilities. Try removing city/state filters, broadening statuses, or enabling includeStudiesWithoutLocations.

Why are contact fields empty?

ClinicalTrials.gov does not publish site contacts for every study or every location. Empty contact arrays mean the source record did not include site-level contacts.

Can I search by NCT ID?

Yes. Add IDs to nctIds. The actor will request those studies directly and flatten their locations.

Related scrapers

Explore other Automation Lab actors at:

• https://apify.com/automation-lab
• https://apify.com/automation-lab/google-maps-lead-finder
• https://apify.com/automation-lab/website-contact-finder

Support

If a run fails or the output does not match your input, open an Apify issue with the run URL and expected result. Include the condition, location, statuses, and NCT IDs you used so the problem can be reproduced.