# ClinicalTrials.gov Study Search (`cheerful_term/clinical-trials`) Actor

Search ClinicalTrials.gov studies by condition, intervention, sponsor, location and status: NCT ID, titles, status, phases, enrollment, start and completion dates, sponsor and collaborators, sites, and summary.

- **URL**: https://apify.com/cheerful_term/clinical-trials.md
- **Developed by:** [Aidan Jude](https://apify.com/cheerful_term) (community)
- **Categories:** Business, Lead generation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$2.00 / 1,000 studies

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## ClinicalTrials.gov Study Search

Search ClinicalTrials.gov studies by condition, intervention, sponsor, location and status: NCT ID, titles, status, phases, enrollment, start and completion dates, sponsor and collaborators, sites, and summary.

### Who it's for

- CROs and site networks finding sponsors recruiting in their area
- Pharma competitive intelligence
- Patient-recruitment and research teams

### Input

| Field | What it does |
|---|---|
| `condition` | **Condition**. e.g. obesity |
| `intervention` | **Intervention**. e.g. semaglutide |
| `sponsor` | **Sponsor**. e.g. Novo Nordisk |
| `location` | **Location**. City, state or country, e.g. Minneapolis |
| `status` | **Overall status**. e.g. RECRUITING, COMPLETED, NOT_YET_RECRUITING |
| `maxItems` | **Max results**. Stop after this many results. Each result is one billed event. |

Example input:

```json
{
  "condition": "obesity",
  "status": "RECRUITING",
  "maxItems": 100
}
```

### Output

One dataset item per result. A real item from a test run:

```json
{
  "nctId": "NCT07331974",
  "title": "Efficacy and Safety of Akkermansia Muciniphila AKM Lab-01 for Overweight and Obesity",
  "officialTitle": "A Randomized, Double-blind, Placebo-controlled Trial to Access the Efficacy and Safety of Akkermansia Muciniphila AKM Lab-01 in Participents With Overweigh and Obesity",
  "status": "RECRUITING",
  "startDate": "2026-06-18",
  "primaryCompletion": "2027-03-31",
  "lastUpdate": "2026-10-09",
  "phases": [
    "NA"
  ],
  "studyType": "INTERVENTIONAL",
  "enrollment": 200,
  "conditions": [
    "Overweight , Obesity"
  ],
  "interventions": [
    "AKM Lab-01",
    "Placebo"
  ],
  "leadSponsor": "Moon (Guangzhou) Biotechnology Co., Ltd.",
  "sponsorClass": "INDUSTRY",
  "collaborators": [],
  "locationCount": 1,
  "locations": [
    "Guangzhou Huangpu District People's Hospital, Guangzhou, Guangdong, China"
  ],
  "summary": "This study is designed as a preliminary investigation to evaluate the weight-loss efficacy and safety of AKM Lab-01 in an overweight or obese population. It is an interventional, radomized, double-blind, placebo-controlled clinical trial. Participants who meet the eligibility criteria will be randomly assigned to receive AKM Lab-01 or a matching placebo. The intervention will be administered once daily for 3 months. Baseline metrics, along with blood, urine, and stool samples, will be collected from participants, before and after the AKM Lab-01 intervention. The analysis will focus on changes in body weight, blood lipids, blood glucose, and gut metagenomic profiles (from stool samples). Furthermore, metabolomic analysis of blood and stool samples will be conducted to explore the potential machanisms through which AMK Lab-01 influences body weight.",
  "url": "https://clinicaltrials.gov/study/NCT07331974"
}
```

Download as JSON, CSV, Excel or via the Apify API.

### Pricing

Pay per result: **$0.002 per study** ($2 per 1,000). No monthly fee. Set a max charge on the run and it stops there. AI agents can run it with agentic payments where Apify enables them.

### Data source

Fetched live at run time from the public source: https://clinicaltrials.gov/api/v2/studies

Public records only. Nothing is fetched behind a login.

### Use it from code or an AI agent

```bash
curl -X POST 'https://api.apify.com/v2/acts/cheerful_term~clinical-trials/run-sync-get-dataset-items?token=YOUR_TOKEN' \
  -H 'Content-Type: application/json' -d '{"condition": "obesity", "status": "RECRUITING", "maxItems": 100}'
```

Part of a set of public-records actors by cheerful_term: https://apify.com/cheerful_term

# Actor input Schema

## `condition` (type: `string`):

e.g. obesity

## `intervention` (type: `string`):

e.g. semaglutide

## `sponsor` (type: `string`):

e.g. Novo Nordisk

## `location` (type: `string`):

City, state or country, e.g. Minneapolis

## `status` (type: `string`):

e.g. RECRUITING, COMPLETED, NOT_YET_RECRUITING

## `maxItems` (type: `integer`):

Stop after this many results. Each result is billed as one event.

## Actor input object example

```json
{
  "condition": "obesity",
  "status": "RECRUITING",
  "maxItems": 100
}
```

# Actor output Schema

## `overview` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "condition": "obesity",
    "status": "RECRUITING",
    "maxItems": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("cheerful_term/clinical-trials").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "condition": "obesity",
    "status": "RECRUITING",
    "maxItems": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("cheerful_term/clinical-trials").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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": "obesity",
  "status": "RECRUITING",
  "maxItems": 100
}' |
apify call cheerful_term/clinical-trials --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,cheerful_term/clinical-trials"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/1w2ExHDmEqZcuFE2g/builds/p46p25CwQO6caK5FR/openapi.json