Clinical Trials Scraper

Here is one real result, with every field the actor returns (the long briefSummary and eligibilityCriteria are truncated; the values shown are real):

{
  "nctId": "NCT01595035",
  "briefTitle": "A Clinical Trial of a Psycho-educational Intervention to Improve Pain Management After Day Surgery",
  "status": "COMPLETED",
  "phase": "NA",
  "conditions": ["Postoperative Pain", "Chronic Pain"],
  "interventions": ["BEHAVIORAL: psychoeducational"],
  "sponsor": "Oslo Metropolitan University",
  "enrollment": 200,
  "startDate": "2012-05",
  "completionDate": "2021-02",
  "studyType": "INTERVENTIONAL",
  "locationCount": 1,
  "countries": ["Norway"],
  "officialTitle": "A Randomized Clinical Trial of a Psycho-educational Intervention to Improve Pain Management After Day Surgery",
  "orgStudyId": "2011/1984",
  "leadSponsorClass": "OTHER",
  "collaborators": ["Oslo University Hospital", "Helse Stavanger HF"],
  "briefSummary": "Evidence indicates that postoperative pain after day surgery is inadequately controlled. [summary truncated]",
  "detailedDescription": null,
  "eligibilityCriteria": "Inclusion Criteria: * > 18 years of age; * able, to read, write, and understand Norwegian; [criteria truncated]",
  "primaryCompletionDate": "2020-02",
  "lastUpdateDate": "2021-03-02",
  "firstPostedDate": "2012-05-09",
  "hasResults": false,
  "allocation": "RANDOMIZED",
  "interventionModel": "PARALLEL",
  "primaryPurpose": "SUPPORTIVE_CARE",
  "masking": "SINGLE",
  "eligibilitySex": "ALL",
  "minimumAge": "18 Years",
  "maximumAge": null,
  "healthyVolunteers": false,
  "centralContacts": [],
  "contactEmails": [],
  "contactPhones": [],
  "investigators": [
    {"name": "Berit Valeberg, PhD", "affiliation": "Oslo Metropolitan University", "role": "PRINCIPAL_INVESTIGATOR"}
  ],
  "locations": [
    {"facility": "Oslo and Akershus University College of Apllied Sciences", "status": null, "city": "Oslo", "state": null, "zip": "N-0130", "country": "Norway", "lat": 59.91273, "lon": 10.74609, "contacts": []}
  ],
  "url": "https://clinicaltrials.gov/study/NCT01595035",
  "source": "ClinicalTrials.gov",
  "observedAt": "2026-08-14T06:17:29.351Z",
  "aiSummary": "This clinical trial studies a new approach to help patients manage pain after day surgery. It focuses on providing personalized support and information to patients, aiming to improve their understanding and adherence to pain relief medications.",
  "aiKeywords": ["postoperative pain", "chronic pain", "psychoeducational intervention", "pain management", "nurse coaching", "academic detailing", "analgesic adherence", "pain intensity", "surgery", "behavioral intervention"],
  "aiField": "Pain Management",
  "aiExtract": {
    "condition": "Postoperative Pain",
    "intervention": "psychoeducational",
    "phase": null,
    "primaryEndpoints": ["higher adherence with the analgesic regimen", "less pain intensity and pain interference with function", "lower severity of side effects compared to the control group"],
    "keyEligibility": ["> 18 years of age", "able to read, write, and understand Norwegian", "scheduled for orthopedic or breast reconstruction surgery", "have a telephone line", "not staying overnight in hospital"]
  }
}

The most complete ClinicalTrials.gov scraper available. It returns every field the study record exposes, including conditions, interventions, sponsor and collaborators, enrollment, phase, status, dates, eligibility, investigators and per-facility locations with coordinates and contacts, plus optional AI plain-language summaries, keywords, therapeutic-area classification and a structured trial profile, and gives you two dozen filters to target exactly the trials you need.

📥 Input · 📤 Output · 💰 Pricing · ▶️ Examples

Table of contents

• What it does
• Quickstart
• Input reference
• Output reference
• Example output record
• Run via API and CLI
• Fetch results
• Billing and limits
• FAQ and troubleshooting

What it does

The actor queries ClinicalTrials.gov, applies the filters you pass as input, paginates through the matching studies, and writes one normalized record per trial to the run's dataset. Each record carries the NCT ID, brief and official titles, status, phase, conditions, interventions, lead sponsor and collaborators, enrollment, study type, start and completion dates, design (allocation, model, purpose, masking), eligibility (sex, age range, healthy-volunteers flag, full criteria text), investigators, and per-facility locations with coordinates and contacts. Missing source values are returned as null.

Optional AI add-ons (paid Apify plans only) add a plain-language lay summary, topical keywords, a therapeutic-area classification, and a structured trial profile (condition, intervention, phase, primary endpoints, key eligibility).

Quickstart

Open the actor, paste this into the input, and press Run. It returns 3 trials matching the keyword with all AI add-ons enabled.

{
  "searchQuery": "melanoma",
  "maxStudies": 3,
  "withAiSummary": true,
  "withAiKeywords": true,
  "withAiField": true,
  "withAiExtract": true
}

Every input is optional. Leave searchQuery empty and refine with the condition, intervention, sponsor, status, phase and location filters instead.

Input reference

Field	Type	Required	Default	Description
searchQuery	string	no	cancer immunotherapy	Free-text keyword matched across the whole study record (condition, intervention, sponsor, title, NCT id).
condition	string	no	(empty)	Filter by medical condition or disease, for example type 2 diabetes.
intervention	string	no	(empty)	Filter by intervention, drug or treatment, for example pembrolizumab.
sponsor	string	no	(empty)	Filter by lead sponsor or collaborator, for example Pfizer.
location	string	no	(empty)	Filter by a location term (country, state, city, facility), for example Boston.
studyStatus	string[]	no	(all)	Keep only these recruitment statuses (for example RECRUITING, COMPLETED, TERMINATED).
phases	string[]	no	(all)	Keep only these phases (EARLY_PHASE1, PHASE1, PHASE2, PHASE3, PHASE4).
studyType	enum	no	(any)	INTERVENTIONAL or OBSERVATIONAL.
sex	enum	no	(all)	Restrict to studies enrolling FEMALE or MALE.
acceptsHealthyVolunteers	boolean	no	false	Keep only studies that accept healthy volunteers.
resultsAvailable	enum	no	(any)	with or without posted study results.
funderTypes	string[]	no	(all)	Keep only these funder types (nih, fed, other_gov, indiv, industry, network, other).
geoLatitude	integer	no	(none)	Latitude of a point to search near (use with longitude and radius).
geoLongitude	integer	no	(none)	Longitude of a point to search near.
geoRadiusMiles	integer	no	50	Search radius in miles around the point.
startDateFrom	string	no	(empty)	Keep studies with start date on or after this date (YYYY-MM-DD).
completionDateTo	string	no	(empty)	Keep studies with completion date on or before this date (YYYY-MM-DD).
maxStudies	integer	no	10	Maximum number of studies to collect.
withAiSummary	boolean	no	false	Paid add-on. Generate a 2 to 3 sentence lay summary. Requires a paid plan. Billed only when a summary is produced.
withAiKeywords	boolean	no	false	Paid add-on. Extract 5 to 10 topical keywords per trial. Requires a paid plan. Billed only when keywords are produced.
withAiField	boolean	no	false	Paid add-on. Classify the therapeutic area / medical field. Requires a paid plan. Billed only when a classification is produced.
withAiExtract	boolean	no	false	Paid add-on. Extract a structured profile (condition, intervention, phase, primary endpoints, key eligibility). Requires a paid plan. Billed only when structured data is produced.

Filters combine with logical AND.

Output reference

One dataset item per trial. Types: string, integer, boolean, string[], object[], object, or null when the source value is absent.

Field	Type	Description
nctId	string	ClinicalTrials.gov NCT identifier (unique per trial).
briefTitle	string	Brief study title.
status	string	Recruitment status, for example COMPLETED.
phase	string	Trial phase, for example PHASE2 or NA.
conditions	string[]	Conditions or diseases studied.
interventions	string[]	Interventions with type prefix, for example DRUG: ....
sponsor	string	Lead sponsor organization.
enrollment	integer	Target or actual enrollment count.
startDate	string	Study start date.
completionDate	string	Study completion date.
studyType	string	INTERVENTIONAL or OBSERVATIONAL.
locationCount	integer	Number of study locations.
countries	string[]	Countries with study sites.
officialTitle	string	Full official study title.
orgStudyId	string	Sponsor's own study ID.
leadSponsorClass	string	Lead sponsor class, for example INDUSTRY, NIH, OTHER.
collaborators	string[]	Collaborating organizations.
briefSummary	string	Brief summary text.
detailedDescription	string	Detailed description, or null.
eligibilityCriteria	string	Full inclusion / exclusion criteria text.
primaryCompletionDate	string	Primary completion date.
lastUpdateDate	string	Date the record was last updated.
firstPostedDate	string	Date the study was first posted.
hasResults	boolean	true when posted results are available.
allocation	string	Allocation method, for example RANDOMIZED.
interventionModel	string	Intervention model, for example PARALLEL.
primaryPurpose	string	Primary purpose, for example TREATMENT.
masking	string	Masking, for example DOUBLE.
eligibilitySex	string	Eligible sex (ALL, FEMALE, MALE).
minimumAge	string	Minimum eligible age.
maximumAge	string	Maximum eligible age, or null.
healthyVolunteers	boolean	true when healthy volunteers are accepted.
centralContacts	object[]	Central study contacts.
contactEmails	string[]	Contact emails parsed from the record.
contactPhones	string[]	Contact phones parsed from the record.
investigators	object[]	Investigators (name, affiliation, role).
locations	object[]	Study locations (facility, status, city, state, zip, country, lat, lon, contacts).
url	string	Study page URL on clinicaltrials.gov.
source	string	Data source name.
aiSummary	string	AI plain-language summary (paid add-on), else absent.
aiKeywords	string[]	AI keywords (paid add-on), else absent.
aiField	string	AI therapeutic area (paid add-on), else absent.
aiExtract	object	AI structured trial profile (paid add-on), else absent.
observedAt	string	ISO 8601 timestamp of when the record was collected.

Example output record

Real record from a live run (input {"searchQuery":"melanoma","maxStudies":3,"withAiSummary":true,"withAiKeywords":true,"withAiField":true,"withAiExtract":true}). Long text fields are truncated; the values shown are real:

{
  "nctId": "NCT01595035",
  "briefTitle": "A Clinical Trial of a Psycho-educational Intervention to Improve Pain Management After Day Surgery",
  "status": "COMPLETED",
  "phase": "NA",
  "conditions": ["Postoperative Pain", "Chronic Pain"],
  "interventions": ["BEHAVIORAL: psychoeducational"],
  "sponsor": "Oslo Metropolitan University",
  "enrollment": 200,
  "studyType": "INTERVENTIONAL",
  "countries": ["Norway"],
  "leadSponsorClass": "OTHER",
  "hasResults": false,
  "allocation": "RANDOMIZED",
  "eligibilitySex": "ALL",
  "minimumAge": "18 Years",
  "url": "https://clinicaltrials.gov/study/NCT01595035",
  "source": "ClinicalTrials.gov",
  "aiField": "Pain Management",
  "aiKeywords": ["postoperative pain", "chronic pain", "psychoeducational intervention", "pain management", "nurse coaching"],
  "observedAt": "2026-08-14T06:17:29.351Z"
}

Run via API and CLI

Start a run and wait for it to finish, then read the dataset. Replace <TOKEN> with your Apify API token.

Run synchronously and get dataset items in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~clinicaltrials-scraper/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"condition":"breast cancer","phases":["PHASE3"],"studyStatus":["RECRUITING"],"maxStudies":50}'

Start a run asynchronously:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~clinicaltrials-scraper/runs?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"sponsor":"Pfizer","location":"United States","maxStudies":200}'

Apify CLI:

apify call scrapers_lat/clinicaltrials-scraper \
  --input '{"intervention":"semaglutide","maxStudies":25}'

Fetch results

Every run writes to a dataset. Fetch items as JSON, CSV, or Excel by changing format:

# JSON
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=json"

# CSV
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=csv"

# Paginate large datasets
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&offset=1000&limit=1000"

<DATASET_ID> is returned as defaultDatasetId in the run object. Use offset and limit to page through large result sets. clean=true drops empty and internal fields.

Billing and limits

• Pay per result. You are charged per trial returned (result event). See the pricing tab for the current per-result price.
• Paid AI add-ons. withAiSummary, withAiKeywords, withAiField and withAiExtract are optional, require a paid Apify plan, and are billed per trial only when they return usable output.
• No charge on failure. If a run errors it does not charge for empty output. Empty runs cost nothing.
• Spend cap respected. Set maxTotalChargeUsd on the run; once reached, the actor stops emitting and charging further billable results.
• Free Apify plans are capped at 10 records per run. Upgrade for higher maxStudies.

FAQ and troubleshooting

A run returned 0 records. Why? The filter combination matched no study. Loosen filters (remove phases or widen the date range). Zero-result runs are not charged.

How do I find actively recruiting trials near a location? Set studyStatus to RECRUITING and either pass a location term or geoLatitude, geoLongitude and geoRadiusMiles.

Do records include site contact emails and phones? Yes, when the study publishes them. contactEmails, contactPhones, centralContacts and per-location contacts are populated from the record; empty arrays mean none were listed.

Why are the AI fields absent? The matching add-on was off, you are on a free account, or the trial had no free text to process. AI fields are never invented.

Why is maximumAge or detailedDescription null? The study did not specify that value. Missing source values are returned as null.

Is this an official government tool? No. This actor is independent and has no affiliation with ClinicalTrials.gov or the NIH. It reads only data that is publicly available through ClinicalTrials.gov. Use it in accordance with the site terms.

Related scrapers

• PubMed Scraper: Biomedical literature records from PubMed.
• openFDA Drug Events & Recalls Scraper: FDA drug adverse events and recalls.
• USA NIH RePORTER Scraper: NIH-funded research projects and grants.
• openFDA Drug Labels Scraper: FDA structured drug label data.
• NPPES NPI Scraper: US healthcare provider NPI records.

More scrapers at scrapers.lat

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Independent tool, not affiliated with ClinicalTrials.gov or the NIH. Accesses only publicly available study data. Use in accordance with the ClinicalTrials.gov terms of service.