ClinicalTrials.gov Scraper — Trials, Sponsors & Contacts

ClinicalTrials.gov Scraper — Clinical Studies, Sponsors, Sites & Principal Investigator Contacts

The definitive ClinicalTrials.gov scraper to search, monitor, and extract exhaustive clinical research studies, trial sites, and key medical investigator contacts. Extract complete study profiles including NCT IDs, study title, recruitment status, development phase, interventional study type, lead pharmaceutical sponsors and institutional collaborators, tested drug/device interventions, targeted disease conditions, patient eligibility criteria, enrollment size, study duration timelines, and verified central/site contact details (full name, direct email, telephone number, and clinic address).

Export research intelligence instantly to JSON, CSV, Excel, XML, or connect via Apify REST API, webhooks, and cloud data workflows.

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⚡ At a glance

Feature	Specification	Description
Coverage Scope	480,000+ Clinical Studies Worldwide	The official international registry of interventional & observational trials
Search Capabilities	Conditions, Sponsors, Drugs, Locations, NCT IDs	Multi-axis querying across diseases, pharmaceutical companies, and molecules
Recruitment Status	Recruiting, Active, Completed, Terminated	Filter precisely for active clinical trials seeking patient enrollment
Contact Intelligence	Central Contacts & Site Principal Investigators	Direct names, email addresses, and phone numbers for trial leaders
Sponsor Classification	Industry, NIH, Federal, Academic/Other	Easily distinguish commercial pharma trials from government/academic grants
Trial Architecture	Phases (Early Phase 1 to Phase 4), Design, Interventions	Comprehensive protocol parameters, blinding, arms, and drug regimens
Geographic Sites	Global Hospital & Clinic Site Directory	Site-by-site facility names, cities, states, postal codes, and countries
Deep Pagination	Unlocked 1,000+ Records per Search	Continuous cursor-based pagination governed by user limits
Speed & Performance	Pure HTTP Datacenter Execution	Under 40 seconds for 200+ enriched clinical studies

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🔎 Why scrape ClinicalTrials.gov?

ClinicalTrials.gov represents the world's most authoritative public registry of clinical research. Maintained by the U.S. National Library of Medicine and the National Institutes of Health (NIH), the database registers interventional drug trials, medical device investigations, and observational studies conducted across more than 200 countries.

For contract research organizations (CROs), pharmaceutical competitive-intelligence analysts, medical device sales teams, biotechnology investors, and patient recruitment specialists, this registry is an irreplaceable strategic asset. Each filing exposes critical market signals: which novel molecules are advancing into Phase 3, which global hospital clinics are currently administering trials, and direct contact details for active trial coordinators.

However, extracting study metadata manually through the web portal is severely constrained. Web searches present one study at a time, disperse contact emails across deep accordions, and fail to offer bulk structured exports.

This ClinicalTrials.gov scraper automates end-to-end trial harvesting. It coordinates multi-axis search queries, traverses pagination cursors, flattens protocol parameters, extracts direct investigator contact records, and exports clean, standardized datasets ready for CRM systems, healthcare data lakes, and business development pipelines.

High-Impact Strategic Applications

• Pharma & CRO Business Development: Generate high-intent lead lists of actively recruiting Phase 1-3 trials with verified central coordinator emails and telephone numbers for clinical trial service pitching.
• Biotech Pipeline Competitive Intelligence: Monitor rival pharmaceutical pipelines (e.g. Pfizer, Novo Nordisk, Eli Lilly, Roche, Novartis) across therapeutic indications to track phase progression and enrollment targets.
• Site Selection & KOL Mapping: Map active clinical trial sites and principal investigators across specific countries and cities to benchmark hospital trial capacity.
• Patient Recruitment Agency Sourcing: Discover recruiting clinical studies by medical condition and geographic radius to match qualified patient cohorts.
• Investment Due Diligence & Market Sizing: Analyze clinical trial velocity, termination rates, and study design parameters across emerging therapeutic mechanisms (e.g., GLP-1 agonists, antibody-drug conjugates).
• Academic Systematic Reviews: Assemble comprehensive trial inventories for meta-analyses and regulatory compliance audits.

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✨ Key Features & Capabilities

• ✅ Six-Way Unified Search: Query simultaneously across conditions/diseases, free-text keywords, sponsors/organizations, interventions/drugs, locations, or direct NCT IDs.
• ✅ Recruitment Status Targeting: Filter specifically by RECRUITING or NOT_YET_RECRUITING status to isolate active studies with verified contact information.
• ✅ Executive Contact Layer: Extracts flat primaryContactName, primaryContactEmail, and primaryContactPhone fields alongside complete centralContacts arrays for rapid outbound outreach.
• ✅ Comprehensive Site Facility Directory: Captures every participating medical center, university hospital, and clinic site with city, state, country, and local site coordinator details (includeLocations).
• ✅ Sponsor Class Categorization: Instantly identify commercial corporate sponsors (INDUSTRY) versus academic institutions and government bodies (NIH, OTHER).
• ✅ Detailed Eligibility Criteria: Ingests gender eligibility (sex), minimum age, maximum age, and healthy volunteer acceptance criteria.
• ✅ Automated Cursor Pagination: Navigates nextPageToken cursors automatically to extract hundreds or thousands of de-duplicated trials per query.
• ✅ Pure HTTP Architecture: Fast datacenter proxy execution delivers low-latency extractions without browser overhead.

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💼 Industry Use Case Playbooks

1. CRO Clinical Service Business Development

Contract Research Organizations providing decentralized trial tech, patient travel coordination, or bioanalytical lab testing need to reach clinical study sponsors at the exact moment a trial is greenlit. By querying status: ["RECRUITING", "NOT_YET_RECRUITING"] within target indications (e.g., oncology, immunology), business development reps obtain direct sponsor contact emails and telephone numbers for immediate outreach.

2. Pharmaceutical Competitive Intelligence Pipeline Tracking

Market access and competitive intelligence teams can track competitor development pipelines. By configuring a recurring query for a competitor's organization name (e.g., AstraZeneca) or specific drug candidate names, analysts receive automated weekly updates on newly initiated trials, primary completion date shifts, and enrollment expansions.

3. Medical Device Territory Mapping & Investigator Sourcing

Makers of medical imaging equipment, specialized catheters, or surgical tools can pinpoint hospital facilities actively running device trials. Searching by interventions: ["Device"] and geographic filters reveals top clinical sites and primary investigator names to prioritize for equipment demonstrations.

4. Health System Trial Matching & Patient Portals

Digital health startups building AI trial-matching services can ingest structured eligibility criteria (minimum age, maximum age, sex, healthy volunteers, condition tags) to automatically match prospective patients against active trial registries.

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📥 Input Parameters

All parameters are optional. Running the actor with empty input performs a demonstration search across diabetes clinical studies.

Parameter	Type	Default	Description
conditions	Array of Strings	["diabetes"]	Diseases, symptoms, or medical conditions to search (e.g. "breast cancer").
searchTerms	Array of Strings	[]	Free-text search terms, titles, or protocol keywords.
sponsors	Array of Strings	[]	Lead sponsor or collaborator organization names (e.g. "Pfizer", "NIH").
interventions	Array of Strings	[]	Investigational drugs, biologics, devices, or procedure names (e.g. "semaglutide").
locations	Array of Strings	[]	Geographic locations (city, state, country) to filter participating trial sites.
status	Array of Select	["RECRUITING"]	Recruitment stage filter (RECRUITING, COMPLETED, ACTIVE_NOT_RECRUITING, etc.).
nctIds	Array of Strings	[]	List of exact NCT identifiers to look up directly (e.g. "NCT07505745").
includeLocations	Boolean	true	Extract complete hospital site directories and per-site contact names.
maxItems	Integer	0	Maximum total studies to extract across all queries. 0 = unlimited.
maxPagesPerQuery	Integer	0	Maximum pagination pages per query (100 studies/page). 0 = auto/unlimited.
proxyConfiguration	Object	{ "useApifyProxy": true }	Apify Proxy configuration. Standard datacenter proxies provide optimal performance.

Sample JSON Configuration: Oncology Recruiting Trials

{
  "conditions": ["non-small cell lung cancer", "melanoma"],
  "status": ["RECRUITING", "NOT_YET_RECRUITING"],
  "includeLocations": true,
  "maxItems": 250,
  "maxPagesPerQuery": 0,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}

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📊 Extracted Data Structure

The scraper delivers clean, strongly typed output where each clinical trial protocol is flattened into analytical columns accompanied by structured site and contact arrays.

🩺 Protocol Identity & Status

Field	Description	Type	Coverage
nctId	Unique ClinicalTrials.gov national registry identifier (e.g., NCT03803787)	String	🟢 High (100%)
title	Brief public trial title	String	🟢 High (100%)
officialTitle	Full scientific official protocol title	String	🟢 High (100%)
acronym	Recognized protocol study acronym or trial name	String	🟡 Conditional (~40%)
url	Direct canonical link to public ClinicalTrials.gov study page	String	🟢 High (100%)
status	Current recruitment status (RECRUITING, COMPLETED, etc.)	String	🟢 High (100%)
studyType	Clinical trial classification (INTERVENTIONAL or OBSERVATIONAL)	String	🟢 High (100%)
phases	Clinical phase array (PHASE1, PHASE2, PHASE3, PHASE4)	Array	🟢 High (~80%)
startDate	Formal clinical trial initiation date (YYYY-MM-DD or Month Year)	String	🟢 High (~98%)
primaryCompletionDate	Expected or actual primary endpoint completion date	String	🟢 High (~95%)
completionDate	Final study completion date across all secondary endpoints	String	🟢 High (~95%)
lastUpdateDate	Registry date when study protocol was last formally updated	String	🟢 High (100%)
enrollmentCount	Target or actual aggregate patient enrollment count	Number	🟢 High (~95%)
hasResults	Boolean indicator whether summary clinical trial results are posted	Boolean	🟢 High (100%)

🏢 Sponsors, Interventions & Disease Targets

Field	Description	Type	Coverage
leadSponsor	Primary sponsoring organization or biopharma company name	String	🟢 High (100%)
leadSponsorClass	Sponsoring organization sector class (INDUSTRY, NIH, OTHER)	String	🟢 High (100%)
collaborators	Array of collaborating pharmaceutical companies, hospitals, or consortia	Array	🟢 High (~65%)
conditions	Medical conditions, diseases, or syndromes targeted by protocol	Array	🟢 High (100%)
interventions	Structured array of investigational interventions with type and name	Array	🟢 High (~90%)
interventionNames	Flattened list of investigational drug and therapy names	Array	🟢 High (~90%)
briefSummary	Natural-language summary of study rationale and clinical objectives	String	🟢 High (100%)

👥 Primary Contacts & Investigator Outreach

Field	Description	Type	Coverage
primaryContactName	Primary central clinical trial coordinator / investigator full name	String	🟢 High (~95% on recruiting)
primaryContactEmail	Direct contact email address for trial inquiries	String	🟢 High (~94% on recruiting)
primaryContactPhone	Direct telephone contact number for study team	String	🟢 High (~94% on recruiting)
centralContacts	Full array of central study contacts with names, roles, phones, and emails	Array	🟢 High (~95% on recruiting)

🏥 Clinical Sites & Geographic Locations

Field	Description	Type	Coverage
locationsCount	Total count of participating medical center and clinic sites	Number	🟢 High (100%)
countries	Unique list of countries hosting participating trial sites	Array	🟢 High (~90%)
locations	Complete array of hospital sites with city, state, country, zip, and site contacts	Array	🟢 High (~90%)
sex	Gender eligibility requirement (ALL, FEMALE, or MALE)	String	🟢 High (100%)
minimumAge	Minimum required patient age for eligibility	String	🟢 High (~90%)
maximumAge	Maximum allowable patient age for eligibility	String	🟢 High (~85%)
healthyVolunteers	Boolean indicator whether healthy volunteers are accepted	Boolean	🟢 High (~85%)
scrapedAt	ISO 8601 extraction timestamp	String	🟢 High (100%)

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💻 Sample Output Record: Interventional Oncology Trial

{
  "nctId": "NCT03803787",
  "title": "Prophylactic Inhaled Steroids to Reduce Radiation Pneumonitis in Lung Cancer Patients",
  "officialTitle": "Prophylactic Inhaled Steroids to Reduce Radiation Pneumonitis Frequency and Severity in Non-small Cell Lung Cancer Patients",
  "acronym": "PNEUMO-STER",
  "url": "https://clinicaltrials.gov/study/NCT03803787",
  "status": "RECRUITING",
  "studyType": "INTERVENTIONAL",
  "phases": ["PHASE2"],
  "startDate": "2018-09-01",
  "primaryCompletionDate": "2026-12-01",
  "completionDate": "2027-12-01",
  "lastUpdateDate": "2026-04-08",
  "enrollmentCount": 72,
  "leadSponsor": "Instituto Nacional de Cancerologia",
  "leadSponsorClass": "OTHER",
  "collaborators": ["National Institute of Respiratory Diseases"],
  "conditions": ["Radiation Pneumonitis", "Non-Small Cell Lung Cancer"],
  "interventions": [
    { "type": "DRUG", "name": "Inhaled budesonide" }
  ],
  "interventionNames": ["Inhaled budesonide"],
  "sex": "ALL",
  "minimumAge": "18 Years",
  "maximumAge": "75 Years",
  "healthyVolunteers": false,
  "briefSummary": "This randomized clinical study aims to assess whether prophylactic treatment with inhaled steroids in patients with locally advanced non-small cell lung carcinoma decreases the severity and frequency of radiation pneumonitis.",
  "primaryContactName": "Oscar Arrieta, MD MSc",
  "primaryContactEmail": "ogarrieta@cancerology.org",
  "primaryContactPhone": "+52-555-628-0400",
  "centralContacts": [
    {
      "name": "Oscar Arrieta, MD MSc",
      "role": "CONTACT",
      "phone": "+52-555-628-0400",
      "email": "ogarrieta@cancerology.org"
    }
  ],
  "locationsCount": 2,
  "countries": ["Mexico"],
  "locations": [
    {
      "facility": "Instituto Nacional de Cancerologia",
      "city": "Mexico City",
      "state": "CDMX",
      "country": "Mexico",
      "zip": "14080",
      "status": "RECRUITING",
      "contacts": [
        {
          "name": "Diana Flores, RN",
          "role": "STUDY_COORDINATOR",
          "phone": "+52-555-628-0400",
          "email": "dflores@cancerology.org"
        }
      ]
    }
  ],
  "hasResults": false,
  "scrapedAt": "2026-11-10T14:45:00.000Z"
}

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🛠️ Step-by-Step Practical Integration Guide

1. Interactive Console Execution

1. Open the actor in the Apify Console.
2. Enter diseases in conditions (e.g. Alzheimer Disease) or companies in sponsors (e.g. Biogen).
3. Set status: ["RECRUITING"] to guarantee high contact email fill rates.
4. Set your desired maxItems target and click Start.

2. Python Pharma Lead Pipeline

from apify_client import ApifyClient
import pandas as pd

client = ApifyClient("YOUR_APIFY_TOKEN")

# Extract actively recruiting cardiovascular trials
run = client.actor("haketa/clinicaltrials-scraper").call(run_input={
    "conditions": ["heart failure"],
    "status": ["RECRUITING"],
    "maxItems": 200,
    "maxPagesPerQuery": 0
})

items = client.dataset(run["defaultDatasetId"]).list_items().items
df = pd.DataFrame(items)

# Filter for trials with verified contact emails
leads = df[df["primaryContactEmail"].str.len() > 0][
    ["nctId", "leadSponsor", "primaryContactName", "primaryContactEmail", "primaryContactPhone"]
]
print(leads.head(10))

3. Node.js & TypeScript Pipeline

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('haketa/clinicaltrials-scraper').call({
    sponsors: ['Pfizer', 'ModernaTX, Inc.'],
    status: ['RECRUITING'],
    maxItems: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const trial of items) {
    console.log(`[${trial.nctId}] ${trial.leadSponsor} -> Contact: ${trial.primaryContactEmail}`);
}

4. cURL & REST API Direct Query

curl -X POST "https://api.apify.com/v2/acts/haketa~clinicaltrials-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "conditions": ["multiple sclerosis"],
    "status": ["RECRUITING"],
    "maxItems": 100,
    "maxPagesPerQuery": 0
  }'

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⚖️ Manual Web Portal vs. ClinicalTrials Scraper

Evaluation Dimension	ClinicalTrials.gov Web Portal	ClinicalTrials.gov Scraper
Extraction Throughput	~10 studies / hour	~500+ studies / minute
Contact Data Extraction	Hidden inside sub-tabs	Direct normalized primaryContactEmail & primaryContactPhone
Site Facility Data	Click each site location	Structured array of hospital locations & coordinators
Batch Query Execution	Single query at a time	Multi-condition & multi-sponsor batch execution
Data Normalization	Unformatted text blocks	Strongly typed JSON/CSV schema ready for analysis
Cloud Automation	Manual download only	Apify Scheduler, Webhooks, Python, Make, Zapier

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💡 Best Practices for Maximum Extraction Yield

• Filter by RECRUITING for Contacts: The registry intentionally publishes active investigator contact details only for studies in RECRUITING or NOT_YET_RECRUITING status. For completed trials, contact details are routinely archived.
• Differentiate Sponsor Classes: Filter on leadSponsorClass: "INDUSTRY" when building commercial B2B sales lists, or leadSponsorClass: "NIH" when monitoring federal grant allocations.
• Extract Entire Corporate Pipelines: Entering a corporate sponsor name (e.g. Novo Nordisk A/S) retrieves all historical, active, and upcoming clinical trials sponsored by that organization.
• Deep Pagination Execution: Setting maxPagesPerQuery: 0 traverses all available pagination tokens until reaching your specified maxItems target.

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❓ Frequently Asked Questions

Does this actor require an official API key or login? No. The scraper runs smoothly without private keys, access tokens, or account credentials.

How does cursor-based pagination work? The scraper requests 100 studies per page and automatically follows the official nextPageToken cursor until your requested maxItems ceiling is reached.

Can I look up trials by NCT number? Yes. You can supply an array of exact NCT identifiers (e.g. ["NCT03803787", "NCT07505745"]) in the nctIds parameter for instant direct lookup.

What proxies are used for scraping? Standard Apify Datacenter proxies are enabled by default and deliver exceptional throughput and zero-friction execution.

Can I exclude site locations to reduce dataset size? Yes. Setting includeLocations: false omits the detailed hospital facility directory, returning a lightweight dataset focused strictly on protocol and sponsor parameters.

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📋 Changelog

Version 1.2 (2026-11)

• Unlocked 1,000+ Deep Pagination: Removed restrictive default page limits; setting maxPagesPerQuery: 0 now enables automatic infinite pagination governed strictly by user-defined item limits.
• Enhanced Empty Input Fallbacks: Integrated multi-indication medical default queries ensuring zero-configuration runs return rich clinical research results without early termination.
• Optimized Contact Normalization: Unified direct email and telephone phone string formatting across central and site contacts.
• Performance Accelerations: Reduced prefill execution duration to sub-minute benchmarks with pure HTTP request streaming.

Version 1.1 (2026-10)

• Added sponsor classification filtering (leadSponsorClass).
• Added site hospital directory and per-site coordinator extraction.
• Standardized eligibility criteria (sex, minimumAge, maximumAge, healthyVolunteers).

Version 1.0 (2026-10)

• Initial release featuring comprehensive clinical study protocol, sponsor, and contact extraction.