# ClinicalTrials.gov Scraper — Studies & Trials (`ponderable_hydrometer/clinicaltrials-scraper`) Actor Search ClinicalTrials.gov (500k+ studies) by condition, drug, sponsor or status. Structured data: phase, enrollment, sponsor, locations. Official free API, no key. - **URL**: https://apify.com/ponderable\_hydrometer/clinicaltrials-scraper.md - **Developed by:** [Ponderable Hydrometer](https://apify.com/ponderable_hydrometer) (community) - **Categories:** Automation, Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 — Studies & Trials Search and extract clinical trial data from **ClinicalTrials.gov** — the US National Library of Medicine's registry of 500,000+ studies. Filter by condition, intervention, sponsor, keyword or recruitment status, and get clean structured data per study. Built on the official ClinicalTrials.gov **v2 API** — free, public, no key, no anti-bot. ### Who it's for - **Pharma & biotech competitive intelligence** — track trials by drug, sponsor or indication. - **CROs** — site selection, enrollment and status monitoring. - **Investors & analysts** — follow pipeline progress and phase transitions. - **Researchers & AI pipelines** — structured trial metadata at scale. ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `condition` | string | — | Condition/disease, e.g. `diabetes` | | `intervention` | string | — | Drug/treatment, e.g. `semaglutide` | | `sponsor` | string | — | Lead sponsor/collaborator, e.g. `Pfizer` | | `searchTerm` | string | — | Free-text search across fields | | `status` | array | — | Filter by status: `RECRUITING`, `ACTIVE_NOT_RECRUITING`, `COMPLETED`, `TERMINATED`, … | | `maxResults` | integer | `200` | Cap on studies returned | Provide at least one of `condition`, `intervention`, `sponsor` or `searchTerm`. ### Output One row per study: ```json { "nctId": "NCT07091500", "title": "GLP-1 Receptor Agonist for Obesity", "status": "RECRUITING", "phases": ["PHASE2"], "studyType": "INTERVENTIONAL", "enrollment": 40, "startDate": "2026-01-15", "completionDate": "2027-06-30", "lastUpdateDate": "2026-07-01", "leadSponsor": "Washington University School of Medicine", "collaborators": ["…"], "conditions": ["Obesity"], "interventions": ["DRUG: Semaglutide"], "sex": "ALL", "minAge": "18 Years", "maxAge": "65 Years", "locationCount": 12, "countries": ["United States"], "url": "https://clinicaltrials.gov/study/NCT07091500" } ```` ### Notes & limits - Official ClinicalTrials.gov v2 API — free, public, no key or anti-bot; paginated automatically. - For advanced field-level queries, use the `searchTerm` field (supports the API's expression syntax) alongside `condition`/`intervention`/`sponsor`. - Public data; you are responsible for compliant use of the output. # Actor input Schema ## `condition` (type: `string`): Condition or disease to search, e.g. "diabetes", "breast cancer". ## `intervention` (type: `string`): Intervention, drug or treatment, e.g. "semaglutide". ## `sponsor` (type: `string`): Lead sponsor or collaborator, e.g. "Pfizer". ## `searchTerm` (type: `string`): General keyword search across study fields. ## `status` (type: `array`): Filter by recruitment status, e.g. RECRUITING, ACTIVE\_NOT\_RECRUITING, COMPLETED, TERMINATED. ## `maxResults` (type: `integer`): Cap on studies returned. ## Actor input object example ```json { "condition": "diabetes", "maxResults": 200 } ``` # 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 = { "condition": "diabetes" }; // Run the Actor and wait for it to finish const run = await client.actor("ponderable_hydrometer/clinicaltrials-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 = { "condition": "diabetes" } # Run the Actor and wait for it to finish run = client.actor("ponderable_hydrometer/clinicaltrials-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 '{ "condition": "diabetes" }' | apify call ponderable_hydrometer/clinicaltrials-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ponderable_hydrometer/clinicaltrials-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ClinicalTrials.gov Scraper — Studies & Trials", "description": "Search ClinicalTrials.gov (500k+ studies) by condition, drug, sponsor or status. Structured data: phase, enrollment, sponsor, locations. Official free API, no key.", "version": "0.1", "x-build-id": "DIKFfk7pangnfXU8Y" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ponderable_hydrometer~clinicaltrials-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ponderable_hydrometer-clinicaltrials-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ponderable_hydrometer~clinicaltrials-scraper/runs": { "post": { "operationId": "runs-sync-ponderable_hydrometer-clinicaltrials-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ponderable_hydrometer~clinicaltrials-scraper/run-sync": { "post": { "operationId": "run-sync-ponderable_hydrometer-clinicaltrials-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "condition": { "title": "Condition / disease", "type": "string", "description": "Condition or disease to search, e.g. \"diabetes\", \"breast cancer\"." }, "intervention": { "title": "Intervention / treatment", "type": "string", "description": "Intervention, drug or treatment, e.g. \"semaglutide\"." }, "sponsor": { "title": "Sponsor", "type": "string", "description": "Lead sponsor or collaborator, e.g. \"Pfizer\"." }, "searchTerm": { "title": "Free-text search", "type": "string", "description": "General keyword search across study fields." }, "status": { "title": "Status filter", "type": "array", "description": "Filter by recruitment status, e.g. RECRUITING, ACTIVE_NOT_RECRUITING, COMPLETED, TERMINATED.", "items": { "type": "string" } }, "maxResults": { "title": "Max results", "minimum": 1, "type": "integer", "description": "Cap on studies returned.", "default": 200 } } }, "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 } } } } } } } } } } ```