# ClinicalTrials.gov Studies Feed — Trials API (`bikram07/clinical-trials-feed`) Actor
Structured clinical-trial records from ClinicalTrials.gov, the official US government registry. Filter by condition, sponsor, status, or phase for a clean JSON feed: title, phase, sponsor, enrollment, dates, locations, eligibility. Zero-config returns recruiting cancer trials.
- **URL**: https://apify.com/bikram07/clinical-trials-feed.md
- **Developed by:** [Bikram](https://apify.com/bikram07) (community)
- **Categories:** Automation, Developer tools, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
Pay per usage
This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage
## 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 Studies Feed — Trials API
Structured, deduplicated **clinical-trial records** pulled directly from **[ClinicalTrials.gov](https://clinicaltrials.gov/)**, the official U.S. National Library of Medicine registry of clinical studies. Instead of parsing the registry's deeply nested API response yourself, you get one clean, flat schema — title, phase, sponsor, enrollment, key dates, locations, and eligibility — ready to export, pipe into a database, or query from an AI agent.
Run it with **zero configuration** to get currently recruiting cancer trials, or filter by condition, free-text term, sponsor, recruitment status, or phase.
### What it does
ClinicalTrials.gov publishes structured study data through its official **data API v2** (`https://clinicaltrials.gov/api/v2/studies`). The raw response is powerful but verbose: every study is a deeply nested `protocolSection` object with a dozen sub-modules, and pagination is cursor-based (you have to follow a `nextPageToken`, not a page number).
This actor handles all of that. It queries the API with your filters, follows the cursor across pages, maps each study from its nested JSON into **one flat record**, deduplicates on `nctId`, sorts by most recently updated, and writes the result to your dataset — ready to export as JSON, CSV, or Excel, feed into a webhook, or read from an AI assistant over MCP.
No API key. No scraping. ClinicalTrials.gov data is **U.S. government public-domain** content, free for commercial use.
### Why a clean trials feed matters
Professional clinical-trial intelligence platforms (Cortellis, Citeline, AdisInsight) cost tens of thousands of dollars a year. A huge long tail of users needs the same underlying registry data but can't justify that spend:
- **Biotech & pharma analysts** — track competitors' pipelines: who is running which phase, in which indication, with how many patients, and when readouts are due.
- **VC & investment associates** — diligence a company's clinical assets, map a therapeutic area's competitive landscape, and monitor status changes before they hit the news.
- **Competitive-intelligence teams** — watch a named sponsor's active and completed trials and get a structured feed instead of manually re-searching the registry.
- **Academics & systematic reviewers** — pull every recruiting trial for a condition into a spreadsheet for screening, without hand-copying from the website.
- **Patient-recruitment & site teams** — find recruiting trials by condition and location to match patients or benchmark enrollment.
- **Data & AI builders** — feed normalized trial records into a RAG pipeline, dashboard, or alerting system.
### Input
Every field is optional. **Empty input `{}` returns currently recruiting cancer trials.**
| Field | Type | Default | Description |
|---|---|---|---|
| `condition` | string | `cancer` | Condition / disease to search (CT.gov `query.cond`). Example: `breast cancer`, `type 2 diabetes`. Defaults to `cancer` when no condition, term, or sponsor is given. |
| `term` | string | — | Free-text search across the whole record (CT.gov `query.term`). Example: `immunotherapy`, `CAR-T`, `semaglutide`. |
| `sponsor` | string | — | Lead-sponsor / collaborator filter (CT.gov `query.spons`). Example: `Pfizer`, `National Cancer Institute`. |
| `overallStatus` | array | `["RECRUITING"]` | Recruitment statuses to include. Valid values: `RECRUITING`, `NOT_YET_RECRUITING`, `ACTIVE_NOT_RECRUITING`, `ENROLLING_BY_INVITATION`, `COMPLETED`, `SUSPENDED`, `TERMINATED`, `WITHDRAWN`, and more. |
| `phase` | string | `""` (any) | Single trial phase: `EARLY_PHASE1`, `PHASE1`, `PHASE2`, `PHASE3`, `PHASE4`, `NA`. |
| `maxStudies` | integer | `200` | Cap on total records output after dedupe. Large pulls are cursor-paginated and throttled to respect the public API. |
#### Zero-config (recruiting cancer trials)
```json
{}
````
#### By condition + phase
```json
{
"condition": "type 2 diabetes",
"phase": "PHASE3",
"overallStatus": ["RECRUITING"],
"maxStudies": 100
}
```
#### By sponsor (full pipeline, any status)
```json
{
"sponsor": "Moderna",
"overallStatus": ["RECRUITING", "ACTIVE_NOT_RECRUITING", "COMPLETED"],
"maxStudies": 500
}
```
### Output
One item per study, deduplicated on `nctId`, sorted by most recently updated. Missing values are `null` — never fabricated.
| Field | Type | Description |
|---|---|---|
| `nctId` | string | ClinicalTrials.gov identifier, e.g. `NCT06649227`. |
| `briefTitle` | string | Short study title. |
| `officialTitle` | string | Full official title. |
| `overallStatus` | string | Recruitment status, e.g. `RECRUITING`. |
| `phase` | string | Trial phase(s), `\|`-joined for multi-phase, e.g. `PHASE2\|PHASE3`. |
| `studyType` | string | `INTERVENTIONAL`, `OBSERVATIONAL`, etc. |
| `conditions` | array | Conditions / diseases studied. |
| `interventions` | array | Interventions as `TYPE: name`, e.g. `DRUG: pembrolizumab`. |
| `sponsorName` | string | Lead sponsor name. |
| `sponsorClass` | string | Sponsor class, e.g. `INDUSTRY`, `NIH`, `OTHER`. |
| `enrollmentCount` | integer | Target / actual enrollment. |
| `startDate` | string | Study start date (`YYYY-MM-DD` or `YYYY-MM`). |
| `primaryCompletionDate` | string | Primary completion date. |
| `completionDate` | string | Overall completion date. |
| `locations` | array | Sites as `{facility, city, country}`. |
| `eligibilityCriteria` | string | Brief inclusion/exclusion excerpt (truncated). |
| `lastUpdatePostDate` | string | Date the record was last updated on CT.gov. |
| `studyUrl` | string | `https://clinicaltrials.gov/study/{nctId}`. |
#### Sample item
```json
{
"nctId": "NCT06649227",
"briefTitle": "Study Investigating the Safety of CD19 CAR-T Cells in Relapsed/Refractory AML",
"overallStatus": "RECRUITING",
"phase": "PHASE1",
"studyType": "INTERVENTIONAL",
"conditions": ["Relapsed Adult AML"],
"interventions": ["DRUG: CAR-T cell therapy"],
"sponsorName": "University Hospital, Lille",
"sponsorClass": "OTHER",
"enrollmentCount": 5,
"startDate": "2025-07-10",
"primaryCompletionDate": "2029-07-10",
"completionDate": "2030-07-10",
"locations": [{ "facility": "CHU de Lille", "city": "Lille", "country": "France" }],
"lastUpdatePostDate": "2025-12-05",
"studyUrl": "https://clinicaltrials.gov/study/NCT06649227"
}
```
### Use cases
- **Pipeline tracking** — schedule a daily run on a sponsor or indication and diff the output to catch new trials and status changes.
- **Competitive landscape** — pull every Phase 2/3 trial for a target into a slide-ready table.
- **Research datasets** — build a screening spreadsheet for a systematic review in one run.
- **AI agents** — connect over MCP so an assistant can answer "what Phase 3 diabetes trials are recruiting?" with live registry data.
### Source
All data comes from the official **[ClinicalTrials.gov data API v2](https://clinicaltrials.gov/data-api/api)**, published by the U.S. National Library of Medicine (NIH). It is public-domain U.S. government data. This actor only reads and reshapes that public data — it adds no editorial content.
### What this actor is NOT
- **Not medical advice.** This is registry metadata for research and intelligence use, not guidance for treatment, enrollment, or any clinical decision. Always consult the official study record and a qualified professional.
- **Not a private or enriched dataset.** It mirrors what ClinicalTrials.gov already publishes. It does not add analysis, predictions, or data not present in the source record.
- **Not real-time push.** Each run is a point-in-time snapshot; schedule runs for monitoring. Records reflect CT.gov's own `lastUpdatePostDate`, which can lag sponsor activity.
- **Not affiliated** with ClinicalTrials.gov, the NIH, or the U.S. National Library of Medicine.
# Actor input Schema
## `condition` (type: `string`):
The condition, disease, or health area to search (CT.gov query.cond). Example: breast cancer, type 2 diabetes, alzheimer. Defaults to cancer when no condition, term, or sponsor is given.
## `term` (type: `string`):
Additional free-text search across the whole record (CT.gov query.term). Example: immunotherapy, CAR-T, semaglutide. Combined with the condition above.
## `sponsor` (type: `string`):
Filter by lead sponsor or collaborator name (CT.gov query.spons). Example: Pfizer, Moderna, National Cancer Institute.
## `overallStatus` (type: `array`):
Which recruitment statuses to include. Defaults to RECRUITING. Pick several to widen the feed.
## `phase` (type: `string`):
Filter to a single trial phase. Leave blank for all phases.
## `maxStudies` (type: `integer`):
Maximum number of clinical-trial records to output (after dedupe). Default 200. Large pulls are cursor-paginated and throttled to respect the public API.
## Actor input object example
```json
{
"condition": "cancer",
"overallStatus": [
"RECRUITING"
],
"phase": "",
"maxStudies": 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": "cancer"
};
// Run the Actor and wait for it to finish
const run = await client.actor("bikram07/clinical-trials-feed").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": "cancer" }
# Run the Actor and wait for it to finish
run = client.actor("bikram07/clinical-trials-feed").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": "cancer"
}' |
apify call bikram07/clinical-trials-feed --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=bikram07/clinical-trials-feed",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "ClinicalTrials.gov Studies Feed — Trials API",
"description": "Structured clinical-trial records from ClinicalTrials.gov, the official US government registry. Filter by condition, sponsor, status, or phase for a clean JSON feed: title, phase, sponsor, enrollment, dates, locations, eligibility. Zero-config returns recruiting cancer trials.",
"version": "0.1",
"x-build-id": "zbS8og6vn205EEg8t"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/bikram07~clinical-trials-feed/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-bikram07-clinical-trials-feed",
"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/bikram07~clinical-trials-feed/runs": {
"post": {
"operationId": "runs-sync-bikram07-clinical-trials-feed",
"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/bikram07~clinical-trials-feed/run-sync": {
"post": {
"operationId": "run-sync-bikram07-clinical-trials-feed",
"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": "The condition, disease, or health area to search (CT.gov query.cond). Example: breast cancer, type 2 diabetes, alzheimer. Defaults to cancer when no condition, term, or sponsor is given."
},
"term": {
"title": "Free-text term (optional)",
"type": "string",
"description": "Additional free-text search across the whole record (CT.gov query.term). Example: immunotherapy, CAR-T, semaglutide. Combined with the condition above."
},
"sponsor": {
"title": "Sponsor / organization (optional)",
"type": "string",
"description": "Filter by lead sponsor or collaborator name (CT.gov query.spons). Example: Pfizer, Moderna, National Cancer Institute."
},
"overallStatus": {
"title": "Recruitment status",
"type": "array",
"description": "Which recruitment statuses to include. Defaults to RECRUITING. Pick several to widen the feed.",
"items": {
"type": "string",
"enum": [
"RECRUITING",
"NOT_YET_RECRUITING",
"ACTIVE_NOT_RECRUITING",
"ENROLLING_BY_INVITATION",
"COMPLETED",
"SUSPENDED",
"TERMINATED",
"WITHDRAWN",
"AVAILABLE",
"NO_LONGER_AVAILABLE",
"TEMPORARILY_NOT_AVAILABLE",
"APPROVED_FOR_MARKETING",
"WITHHELD",
"UNKNOWN"
],
"enumTitles": [
"Recruiting",
"Not yet recruiting",
"Active, not recruiting",
"Enrolling by invitation",
"Completed",
"Suspended",
"Terminated",
"Withdrawn",
"Available",
"No longer available",
"Temporarily not available",
"Approved for marketing",
"Withheld",
"Unknown"
]
},
"default": [
"RECRUITING"
]
},
"phase": {
"title": "Trial phase (optional)",
"enum": [
"",
"EARLY_PHASE1",
"PHASE1",
"PHASE2",
"PHASE3",
"PHASE4",
"NA"
],
"type": "string",
"description": "Filter to a single trial phase. Leave blank for all phases.",
"default": ""
},
"maxStudies": {
"title": "Max studies",
"minimum": 1,
"maximum": 10000,
"type": "integer",
"description": "Maximum number of clinical-trial records to output (after dedupe). Default 200. Large pulls are cursor-paginated and throttled to respect the public API.",
"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
}
}
}
}
}
}
}
}
}
}
```