# US ClinicalTrials.gov Biotech & Pharma Study Radar (`b2b-quant-apis/us-clinical-trials-biotech-radar`) Actor

B2B clinical trials intelligence and biotech sponsor lead generator powered by the official U.S. NIH ClinicalTrials.gov API v2. Extracts recruiting studies, pharma sponsors, phases, drug interventions, enrollment counts, and site contacts with LLM-ready Markdown briefs.

- **URL**: https://apify.com/b2b-quant-apis/us-clinical-trials-biotech-radar.md
- **Developed by:** [Jesley Tassili de Oliveira Aguileira](https://apify.com/b2b-quant-apis) (community)
- **Categories:** AI, Lead generation, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$40.00 / 1,000 clinical trial & biotech sponsor extracteds

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

## US ClinicalTrials.gov Biotech, Pharma Sponsor & Recruiting Study Radar

Extract structured clinical trial pipelines, biotech/pharma sponsors, drug interventions, enrollment metrics, central contacts, and hospital site counts directly from the official **U.S. National Library of Medicine / NIH ClinicalTrials.gov REST API v2** (`https://clinicaltrials.gov/api/v2/studies`).

Designed for **Contract Research Organizations (CROs)**, **Biotech Venture Capital & Private Equity analysts**, **Pharma Business Development teams**, **Clinical Recruitment agencies**, and **AI Healthcare Research Agents (MCP-ready)**.

***

### Key Features

- **Official NIH ClinicalTrials.gov v2 Integration**: Real-time access to registered clinical studies without fragile HTML scraping.
- **Biotech & Pharma Sponsor Profiling**: Identifies `leadSponsorName`, `leadSponsorClass` (`INDUSTRY`, `NIH`, `FED`, `OTHER`), and collaborating institutions.
- **Pipeline & Intervention Intelligence**: Extracts trial `phases` (`PHASE1`, `PHASE2`, `PHASE3`, `PHASE4`), `enrollmentCount`, target `conditions`, and drug/device/biological `interventions`.
- **Site & Central Contact Extraction**: Captures `centralContacts` (names, roles, phone numbers, emails) and total participating clinical locations (`locationsCount` + site sample).
- **LLM-Ready Markdown Trial Brief**: Automatically generates a clean, structured `markdownTrialBrief` per study for RAG pipelines, AI agents, and automated CRM enrichment.
- **MCP Server Enabled**: Native Model Context Protocol (`mcpServer: true`) compatibility for Claude, Cursor, and autonomous research workflows.

***

### Input Parameters

| Field | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `condition` | `string` | `"Diabetes"` | Disease, medical condition, or therapeutic area query (e.g., `"Diabetes"`, `"Oncology"`, `"Obesity"`). |
| `overallStatus` | `string` | `"RECRUITING"` | Recruitment status filter: `RECRUITING`, `NOT_YET_RECRUITING`, `ACTIVE_NOT_RECRUITING`, `COMPLETED`, or `ALL`. |
| `maxResults` | `integer` | `10` | Maximum number of studies to return (`1` to `100`). |

***

### Output Dataset Example

```json
{
  "nctId": "NCT06123456",
  "briefTitle": "Phase 2 Study of GLP-1/GIP Dual Agonist in Type 2 Diabetes Mellitus",
  "officialTitle": "A Randomized, Double-Blind, Placebo-Controlled Phase 2 Trial Evaluating Efficacy and Safety in Adults With Type 2 Diabetes",
  "overallStatus": "RECRUITING",
  "leadSponsorName": "Apex Biotech Therapeutics Inc.",
  "leadSponsorClass": "INDUSTRY",
  "phases": ["PHASE2"],
  "enrollmentCount": 240,
  "conditions": ["Type 2 Diabetes Mellitus", "Metabolic Syndrome"],
  "interventions": [
    {
      "type": "DRUG",
      "name": "ABT-890 Dual Agonist",
      "description": "Subcutaneous weekly injection"
    }
  ],
  "centralContacts": [
    {
      "name": "Clinical Trials Operations Desk",
      "role": "CONTACT",
      "phone": "+1-800-555-0199",
      "email": "trials@apexbiotech.example.com"
    }
  ],
  "locationsCount": 18,
  "studyUrl": "https://clinicaltrials.gov/study/NCT06123456",
  "markdownTrialBrief": "## [NCT06123456] Phase 2 Study of GLP-1/GIP Dual Agonist in Type 2 Diabetes Mellitus\n..."
}
```

# Actor input Schema

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

Disease, medical condition, or therapeutic area query (e.g., Diabetes, Non-Small Cell Lung Cancer, Obesity, Alzheimer).

## `overallStatus` (type: `string`):

Filter clinical studies by current recruitment status on ClinicalTrials.gov.

## `maxResults` (type: `integer`):

Maximum number of clinical trial records to fetch (1 to 100).

## Actor input object example

```json
{
  "condition": "Diabetes",
  "overallStatus": "RECRUITING",
  "maxResults": 10
}
```

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

// Prepare Actor input
const input = {
    "condition": "Diabetes"
};

// Run the Actor and wait for it to finish
const run = await client.actor("b2b-quant-apis/us-clinical-trials-biotech-radar").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": "Diabetes" }

# Run the Actor and wait for it to finish
run = client.actor("b2b-quant-apis/us-clinical-trials-biotech-radar").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": "Diabetes"
}' |
apify call b2b-quant-apis/us-clinical-trials-biotech-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,b2b-quant-apis/us-clinical-trials-biotech-radar"
        }
    }
}
```

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/mJ83w3bctxEHOoXx3/builds/HKBvDPz53QVCmuDyQ/openapi.json