# ClinicalTrials.gov Scraper (`datamule/clinicaltrials-gov-scraper`) Actor Scrape clinical-trial records from the official ClinicalTrials.gov v2 REST API. Query by condition, intervention, sponsor, status, phase or free text. One record per study — NCT id, title, status, phase, sponsor, conditions, interventions, enrollment, dates, locations + the raw study. Pay per study. - **URL**: https://apify.com/datamule/clinicaltrials-gov-scraper.md - **Developed by:** [Datamule](https://apify.com/datamule) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.35 / 1,000 study returneds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## ClinicalTrials.gov Scraper Scrape clinical-trial registry records from the **official ClinicalTrials.gov v2 REST API** (`https://clinicaltrials.gov/api/v2/studies`) — the U.S. NIH registry of clinical studies. No API key, no login. One clean dataset record per study, with a flat set of normalized columns plus the complete raw study object so nothing is lost. ### What it does Query the registry by any combination of filters (the API ANDs them together): | Input | API field | Example | |-------|-----------|---------| | `query` | free-text over the whole record | `GLP-1`, `long COVID` | | `condition` | condition / disease | `type 2 diabetes` | | `intervention` | intervention / drug / device | `semaglutide` | | `sponsor` | lead sponsor / collaborator | `Pfizer` | | `titles` | words in the study title | `migraine prevention` | | `nctId` | a specific study id | `NCT03470961` | | `status` | recruitment status (multi-select) | `RECRUITING`, `COMPLETED` | | `phase` | trial phase | `PHASE3` | | `studyType` | interventional / observational | `INTERVENTIONAL` | | `sort` | result ordering | `LastUpdatePostDate:desc` | `maxResults` caps how many studies you get; the actor paginates automatically (opaque `nextPageToken`, up to 1000 studies per request) until it reaches the cap or the result set is exhausted. ### Output One dataset record per study. Normalized convenience columns: `nctId`, `briefTitle`, `officialTitle`, `acronym`, `overallStatus`, `studyType`, `phases`, `phase`, `conditions`, `interventions`, `interventionTypes`, `leadSponsor`, `leadSponsorClass`, `collaborators`, `enrollment`, `startDate`, `primaryCompletionDate`, `completionDate`, `lastUpdatePostDate`, `locations` (facility / city / state / country), `locationCountries`, `hasResults`, `studyUrl` …plus **`raw`** — the complete, untouched study object from the API (`protocolSection`, `derivedSection`, …) so any field not surfaced above is still available. ### Example input ```json { "condition": "diabetes", "intervention": "metformin", "status": ["RECRUITING"], "phase": "PHASE3", "maxResults": 200, "sort": "LastUpdatePostDate:desc" } ```` A query that matches nothing returns **0 records and succeeds** (never an error). ### Pricing Pay-per-event: charged per study returned. ### Source Data comes from the U.S. National Library of Medicine's ClinicalTrials.gov v2 API (). ClinicalTrials.gov data is in the public domain. This actor is an independent tool and is not affiliated with or endorsed by NIH / NLM. # Actor input Schema ## `query` (type: `string`): Free-text search across the whole study record (maps to the API's query.term). e.g. "GLP-1", "long COVID", "CAR-T". Combine with the field-specific filters below — the API ANDs them together. Leave everything empty to return the most recent studies. ## `condition` (type: `string`): Condition or disease being studied (query.cond). e.g. "type 2 diabetes", "breast cancer", "alzheimer". ## `intervention` (type: `string`): Intervention, drug, device or treatment (query.intr). e.g. "metformin", "semaglutide", "pacemaker". ## `sponsor` (type: `string`): Lead sponsor or collaborator organisation (query.spons). e.g. "Pfizer", "Mayo Clinic", "National Cancer Institute". ## `titles` (type: `string`): Words that must appear in the brief or official study title (query.titles). e.g. "migraine prevention". ## `nctId` (type: `string`): Look up a specific study by its ClinicalTrials.gov identifier or org study id (query.id). e.g. "NCT03470961". ## `status` (type: `array`): Filter to one or more overall recruitment statuses (filter.overallStatus). Leave empty for any status. ## `phase` (type: `string`): Filter to a single clinical-trial phase (aggFilters phase). Leave empty for any phase. ## `studyType` (type: `string`): Filter to interventional or observational studies (aggFilters studyType). Leave empty for any type. ## `sort` (type: `string`): Sort results by a field. e.g. LastUpdatePostDate:desc (most recently updated first), EnrollmentCount:desc, StartDate:desc. Leave empty for the API's default relevance order. ## `maxResults` (type: `integer`): Maximum number of studies to return. The actor paginates automatically at up to 1000 per request until this many are collected or the result set is exhausted. ## `pageSize` (type: `integer`): Studies fetched per API request (1–1000). Larger pages = fewer requests. Usually leave at the default. ## Actor input object example ```json { "query": "diabetes", "status": [], "phase": "", "studyType": "", "maxResults": 100, "pageSize": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "query": "diabetes", "condition": "", "intervention": "", "sponsor": "", "titles": "", "nctId": "", "sort": "", "maxResults": 100, "pageSize": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("datamule/clinicaltrials-gov-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": "diabetes", "condition": "", "intervention": "", "sponsor": "", "titles": "", "nctId": "", "sort": "", "maxResults": 100, "pageSize": 100, } # Run the Actor and wait for it to finish run = client.actor("datamule/clinicaltrials-gov-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "diabetes", "condition": "", "intervention": "", "sponsor": "", "titles": "", "nctId": "", "sort": "", "maxResults": 100, "pageSize": 100 }' | apify call datamule/clinicaltrials-gov-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datamule/clinicaltrials-gov-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ClinicalTrials.gov Scraper", "description": "Scrape clinical-trial records from the official ClinicalTrials.gov v2 REST API. Query by condition, intervention, sponsor, status, phase or free text. One record per study — NCT id, title, status, phase, sponsor, conditions, interventions, enrollment, dates, locations + the raw study. Pay per study.", "version": "0.1", "x-build-id": "IhRwnK3JIb1hLdh2J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datamule~clinicaltrials-gov-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datamule-clinicaltrials-gov-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datamule~clinicaltrials-gov-scraper/runs": { "post": { "operationId": "runs-sync-datamule-clinicaltrials-gov-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datamule~clinicaltrials-gov-scraper/run-sync": { "post": { "operationId": "run-sync-datamule-clinicaltrials-gov-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "query": { "title": "Search term (free text)", "type": "string", "description": "Free-text search across the whole study record (maps to the API's query.term). e.g. \"GLP-1\", \"long COVID\", \"CAR-T\". Combine with the field-specific filters below — the API ANDs them together. Leave everything empty to return the most recent studies." }, "condition": { "title": "Condition / disease", "type": "string", "description": "Condition or disease being studied (query.cond). e.g. \"type 2 diabetes\", \"breast cancer\", \"alzheimer\"." }, "intervention": { "title": "Intervention / treatment", "type": "string", "description": "Intervention, drug, device or treatment (query.intr). e.g. \"metformin\", \"semaglutide\", \"pacemaker\"." }, "sponsor": { "title": "Sponsor / collaborator", "type": "string", "description": "Lead sponsor or collaborator organisation (query.spons). e.g. \"Pfizer\", \"Mayo Clinic\", \"National Cancer Institute\"." }, "titles": { "title": "Words in title", "type": "string", "description": "Words that must appear in the brief or official study title (query.titles). e.g. \"migraine prevention\"." }, "nctId": { "title": "NCT id", "type": "string", "description": "Look up a specific study by its ClinicalTrials.gov identifier or org study id (query.id). e.g. \"NCT03470961\"." }, "status": { "title": "Recruitment status", "type": "array", "description": "Filter to one or more overall recruitment statuses (filter.overallStatus). Leave empty for any status.", "items": { "type": "string", "enum": [ "RECRUITING", "NOT_YET_RECRUITING", "ENROLLING_BY_INVITATION", "ACTIVE_NOT_RECRUITING", "COMPLETED", "SUSPENDED", "TERMINATED", "WITHDRAWN", "UNKNOWN", "AVAILABLE", "NO_LONGER_AVAILABLE", "TEMPORARILY_NOT_AVAILABLE", "APPROVED_FOR_MARKETING", "WITHHELD" ], "enumTitles": [ "Recruiting", "Not yet recruiting", "Enrolling by invitation", "Active, not recruiting", "Completed", "Suspended", "Terminated", "Withdrawn", "Unknown", "Available (expanded access)", "No longer available", "Temporarily not available", "Approved for marketing", "Withheld" ] }, "default": [] }, "phase": { "title": "Trial phase", "enum": [ "", "EARLY_PHASE1", "PHASE1", "PHASE2", "PHASE3", "PHASE4" ], "type": "string", "description": "Filter to a single clinical-trial phase (aggFilters phase). Leave empty for any phase.", "default": "" }, "studyType": { "title": "Study type", "enum": [ "", "INTERVENTIONAL", "OBSERVATIONAL" ], "type": "string", "description": "Filter to interventional or observational studies (aggFilters studyType). Leave empty for any type.", "default": "" }, "sort": { "title": "Sort", "type": "string", "description": "Sort results by a field. e.g. LastUpdatePostDate:desc (most recently updated first), EnrollmentCount:desc, StartDate:desc. Leave empty for the API's default relevance order." }, "maxResults": { "title": "Max results", "minimum": 1, "type": "integer", "description": "Maximum number of studies to return. The actor paginates automatically at up to 1000 per request until this many are collected or the result set is exhausted.", "default": 100 }, "pageSize": { "title": "Page size", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Studies fetched per API request (1–1000). Larger pages = fewer requests. Usually leave at the default.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```