ClinicalTrials.gov Scraper: Studies by Condition, Drug or Sponsor

$1 per 1,000 studies. Platform usage included. No rental, no minimum.

Open it in Apify Console

New to Apify? [Create a free account](https://www.apify.com?fpr=ymnoit) (referral link). Runs from a free plan account return the first 10 results; any paid plan returns everything you ask for, up to your limit.

What it costs

Studies	Price
1,000	$1.00
10,000	$10.00
100,000	$100.00

Plus $0.001 per run. One flat price, platform usage included, so there is no separate compute or proxy bill. A weekly pull of 300 recently updated studies on one disease costs about $0.30 per run, or about $1.20 a month.

Why use it

• Search the way trial teams do. Condition, drug, sponsor, free text, place, country, status, phase, study type, start dates and "updated since", all in one input.
• Monitoring. Set updatedSince and sort by recently updated to see only the studies that changed since your last run.
• Clean rows. Dates, sponsor, enrollment, phases, interventions, primary outcomes and eligibility basics come as flat fields, not the API's nested sections.
• Optional detail. Turn on includeLocations for every study site with coordinates, or includeLongText for the detailed description and full eligibility criteria.
• Official API, no key. Data comes straight from the ClinicalTrials.gov API v2.

Quick start

1. Open the actor, type a condition such as diabetes, choose a status, press Start.
2. Or paste this input:

{ "condition": "breast cancer", "status": ["RECRUITING"], "phases": ["PHASE2", "PHASE3"], "countries": ["India"], "maxItems": 200 }

3. Download the results as JSON, CSV or Excel, or read them through the API.

Use it from code

curl -X POST "https://api.apify.com/v2/acts/one_dollar_store~clinical-trials-search/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"condition": "diabetes", "status": ["RECRUITING"], "maxItems": 100}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("one_dollar_store/clinical-trials-search").call(
    run_input={"condition": "diabetes", "status": ["RECRUITING"], "maxItems": 100}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["nctId"], item["status"], item["leadSponsor"], item["title"])

Use it from an AI assistant

Claude, ChatGPT, Cursor and other assistants can call this actor through Apify's MCP server. Add it with this server address:

https://mcp.apify.com?tools=one_dollar_store/clinical-trials-search

Then ask, for example: "List 30 recruiting phase 3 trials for lung cancer in Germany with their sponsors."

Switching from another ClinicalTrials.gov actor

Most ClinicalTrials actors take a condition, a sponsor or a search term and a result limit. Here they are condition, sponsor, searchTerm and maxItems. The core output fields are nctId, title, status, phases, conditions, leadSponsor, enrollment and startDate.

Input

Field	Type	Default	What it does
condition	text	none	Disease or condition. You can write asthma OR COPD.
intervention	text	none	Drug, device or procedure.
sponsor	text	none	Lead sponsor or collaborator.
searchTerm	text	none	Free text across the whole record.
location	text	none	City, state, hospital or country name.
countries	list of text	none	Only studies with a site in these countries.
status	list	all	RECRUITING, NOT_YET_RECRUITING, ACTIVE_NOT_RECRUITING, ENROLLING_BY_INVITATION, COMPLETED, TERMINATED, WITHDRAWN, SUSPENDED, UNKNOWN.
studyType	text	any	INTERVENTIONAL, OBSERVATIONAL or EXPANDED_ACCESS.
phases	list	all	EARLY_PHASE1, PHASE1, PHASE2, PHASE3, PHASE4, NA.
onlyWithResults	true or false	false	Only studies with results posted.
startDateFrom, startDateTo	text	none	Study start date range, as 2024-01-31 or 2024-01.
updatedSince	text	none	Only records changed on or after this date.
sort	text	relevance	relevance, updated, posted or enrollment.
includeLocations	true or false	false	Adds every site with city, country, status and coordinates.
includeLongText	true or false	false	Adds the detailed description and eligibility criteria.
maxItems	number	100	Total studies for the run. Minimum 10.

Give at least one search or filter. Example:

{
  "condition": "asthma OR COPD",
  "countries": ["India", "United States"],
  "phases": ["PHASE2", "PHASE3"],
  "onlyWithResults": true,
  "updatedSince": "2025-01-01",
  "sort": "updated",
  "maxItems": 500
}

Output fields

Field	Meaning
nctId, url, orgStudyId	The NCT number, the study page and the sponsor's own study id.
title, officialTitle, briefSummary	Short title, full title and the brief summary.
status, statusVerifiedDate, whyStopped	Recruitment status, when it was last verified and the reason a study stopped.
studyType, phases, design	Type, phases, and allocation, intervention model, primary purpose and masking.
conditions, keywords	Conditions studied and keywords.
interventions	Type, name and description of each intervention.
primaryOutcomes	Primary outcome measures with their time frames.
leadSponsor, sponsorClass, collaborators	Sponsor, its class (industry, NIH, other) and collaborators.
enrollment, enrollmentType	Number of participants and whether it is estimated or actual.
startDate, primaryCompletionDate, completionDate	Study dates as 2025-02-07 or 2025-02.
firstPostedDate, lastUpdatePostedDate, resultsFirstPostedDate, hasResults	Registry dates and whether results are posted.
sex, minimumAge, maximumAge, ageGroups, healthyVolunteers	Eligibility basics.
locationCount, countries	Number of sites and the countries they are in.
locations, detailedDescription, eligibilityCriteria	Only with the matching switch on.

Fields a study does not have are left out.

Sample results

Real rows from a test run on 9 October 2026, with some fields left out to keep them short.

[
  {"nctId": "NCT07394114", "title": "A Study of HDM1005 in Participants With Type 2 Diabetes Not Controlled With Diet and Exercise Alone",
   "status": "RECRUITING", "phases": ["PHASE3"], "conditions": ["Type 2 Diabetes"],
   "interventions": [{"type": "DRUG", "name": "HDM1005 1"}, {"type": "DRUG", "name": "HDM1005 2"}],
   "leadSponsor": "Hangzhou Zhongmei Huadong Pharmaceutical Co., Ltd.", "sponsorClass": "INDUSTRY", "enrollment": 240, "enrollmentType": "ESTIMATED",
   "startDate": "2026-02-24", "primaryCompletionDate": "2027-08-28", "lastUpdatePostedDate": "2026-02-09", "countries": ["China"],
   "url": "https://clinicaltrials.gov/study/NCT07394114"},
  {"nctId": "NCT07417865", "title": "ECHO Diabetes FQHC", "status": "RECRUITING", "conditions": ["Diabetes"],
   "interventions": [{"type": "BEHAVIORAL", "name": "ECHO Diabetes tele-education"}],
   "leadSponsor": "University of Florida", "sponsorClass": "OTHER", "enrollment": 18, "enrollmentType": "ESTIMATED",
   "startDate": "2026-01-22", "primaryCompletionDate": "2028-07-31", "lastUpdatePostedDate": "2026-02-18", "countries": ["United States"],
   "url": "https://clinicaltrials.gov/study/NCT07417865"}
]

Limits

• Only registered studies. The data is what sponsors and investigators entered in ClinicalTrials.gov. Many trials run without being registered, and the actor cannot see those.
• Related words match too. The site searches synonyms and related terms. A search for diabetes also returns studies that mention it in passing, such as obesity studies for people without diabetes. Narrow it with condition plus status, phases or countries.
• Sites make rows longer. includeLocations adds one entry per site, and some large studies have hundreds. Leave it off if you only need counts: locationCount and countries are always there.
• Dates can be partial. Some studies give only a year and month, so a date can look like 2025-02.
• Order. Without sort, rows come in the site's own ranking, which is not strictly by date.
• Speed. A test run of 50 studies took 4 to 5 seconds. Results are written one row at a time, so big runs take longer; we have not timed a run larger than 50 studies on this actor.
• Not medical advice. Study records are not a guide to treatment. Ask a doctor.

FAQ

How much does it cost to scrape 10,000 clinical trials? $10, plus $0.001 for each run.

Do I pay for compute or proxy on top? No. Platform usage is included in the $1 per 1,000 price. The ClinicalTrials.gov API is read directly, so no proxy is used.

Where does the data come from? From the official ClinicalTrials.gov API v2, run by the US National Library of Medicine. No key and no login are needed, and the actor reads it in pages at a modest pace.

How do I find only new or changed studies? Set updatedSince to the date of your last run and sort to updated. Use nctId to drop studies you already have.

How do I get every site of a study? Turn on includeLocations. Each study then has a locations list with facility, city, state, ZIP, country, status and coordinates.

Can I search for trials in one country? Yes. Put the country in countries, for example India. Write the English name as ClinicalTrials.gov spells it, such as United States or South Korea.

Is it legal? The actor reads public data only, with no login. ClinicalTrials.gov states that the information in it is public. How you use it is up to you: follow the site's terms, privacy rules and the law where you live.

Is this an official ClinicalTrials.gov product? No. It is an independent tool and is not affiliated with or endorsed by ClinicalTrials.gov, the National Library of Medicine or the US government.

Do I need an Apify account? Yes. Actors run from an Apify account, and a free account is enough to start: it includes $5 of platform usage every month. You can sign up here. This is a referral link and it costs you nothing.

Is there a limit on the free plan? Yes. A run started from a free plan account delivers the first 10 results, then ends with a message and a link to the plans. Any paid plan returns everything you ask for, up to your own limit. The price per result is the same on every plan.

More from The One Dollar Store

Every actor here costs $1 per 1,000 results, platform usage included. See the whole store: https://apify.com/one_dollar_store

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Changelog

• October 2026: first release.