# ClinicalTrials.gov PI Emails + NIH Grant & CRO Signals (`grandiose_envelope_0fj/clinical-trials-leads-scraper`) Actor

🔗 \[Multi-Source Cross-Joined] Extract recruiting clinical trials from ClinicalTrials.gov v2 + Cross-Join NIH RePORTER grant funding ($) + Harvest ALL multi-center PI direct emails/phones + Compute CRO Patient Recruitment Bottleneck & Site Burden scores.

- **URL**: https://apify.com/grandiose_envelope_0fj/clinical-trials-leads-scraper.md
- **Developed by:** [Olive LI](https://apify.com/grandiose_envelope_0fj) (community)
- **Categories:** Lead generation, Agents, Integrations
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.50 / 1,000 cross-joined enriched lead / records

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 Recruiting Trials + NIH Grant & CRO Bottleneck Intelligence (`clinical-trials-leads-scraper`)

> **100/100 Buyer-Ready Scale Certified** · **Entity-Level Relational `LEFT JOIN`: `ClinicalTrials.gov v2 Interventional Studies` ⟕ `Sponsor Total Pipeline Depth API` ⟕ `NIH RePORTER v2 Grant Funding`**

***

### 1. Who Buys This Data & How They Use It

| Paying Buyer Persona | Target Product / Offer | Exact CRM / Outreach Workflow |
| :--- | :--- | :--- |
| **Patient Recruitment Agencies** (AutoCruitment, StudyKIK, Clariness) | Digital patient pre-screening & enrollment (`$1,500–$5,000` per randomized patient) | Filter `patients_per_site_burden_num >= 30` and import `contact_email`, `contact_salutation` (`Dr. Gabel`), `sponsor_clean_name`, and `outreach_icebreaker` directly into **Instantly.ai / Smartlead**. |
| **Boutique Clinical CROs & eClinical SaaS** (EDC, eTMF, CTMS, ePRO vendors) | Full-service trial monitoring & software (`$50k–$500k` per study) | Filter `sponsor_commercial_tier == "COMMERCIAL_BIOTECH_PHARMA"` + `sponsor_total_trials_count_num <= 10` (Emerging Biotech sponsors without large internal clinical ops teams). |
| **Central Labs & Cold-Chain Bio-Couriers** (Marken, World Courier) | Specimen logistics & biomarker assays | Filter multi-center trials (`clinical_sites_count_num >= 3`) and reach out to `contact_email` + `secondary_site_emails`. |

***

### 2. Relational `LEFT JOIN` Architecture

1. **Primary Entity (`1 Row = 1 Active Interventional Clinical Trial`, `nct_id`)**:
   - Prioritizes active **Interventional** Drug, Biologic, and Device trials (`AREA[StudyType]INTERVENTIONAL`), harvesting both the Central Study Contact and all individual Clinical Site contacts.
2. **Relational `LEFT JOIN #1` (Sponsor Pipeline Depth via `query.spons` `countTotal=true`)**:
   - Queries ClinicalTrials.gov for the exact total number of trials sponsored by `lead_sponsor_legal_name` (`sponsor_total_trials_count_num`), distinguishing **Emerging Single-Asset Biotech Startups** from mega-pharma/university hospitals.
3. **Relational `LEFT JOIN #2` (`ClinicalTrials.gov` ⟕ `NIH RePORTER v2 API`)**:
   - Queries NIH RePORTER across FY2024–2026 by `(contact_first_name, contact_last_name)` and `lead_sponsor_legal_name` to extract active federal grant funding (`nih_funding_usd_num`).

***

### 3. 7-Gate Buyer-Ready Output Format (`33` Plug-and-Play Columns)

- **Gate 1 (Entity Purity)**: `nct_id` (`NCT...`, 1 Row = 1 Recruiting Interventional Trial).
- **Gate 2 (Clean Split Decision-Maker Name)**: `contact_first_name` (`"Kelsey"`), `contact_last_name` (`"Gabel"`), `contact_credential` (`"PhD"`), `contact_salutation` (`"Dr. Gabel"`).
- **Gate 3 (Clean Sponsor Name)**: `sponsor_clean_name` stripped of `INC/LLC/CORP` and converted from ALL-CAPS when needed.
- **Gate 4 (Atomic Contact Channels)**: Single primary `contact_email`, `contact_phone_e164`, `contact_phone_formatted`, plus separate `secondary_site_emails`.
- **Gate 5 (Sortable Numeric Columns)**: `enrollment_target_num`, `clinical_sites_count_num`, `patients_per_site_burden_num`, `sponsor_total_trials_count_num`, `nih_funding_usd_num`.
- **Gate 6 (Atomic Geography & ISO Dates)**: `primary_site_facility`, `primary_site_city`, `primary_site_state`, `primary_site_country`, plus strict ISO `YYYY-MM-DD` `start_date` and `primary_completion_date`.
- **Gate 7 (Plug-and-Play Outreach Hook)**: `outreach_icebreaker` referencing the exact NCT ID, phase, condition, enrollment target, and per-site patient burden.

# Actor input Schema

## `queryTerm` (type: `string`):

Search condition, drug, target, or therapeutic area (e.g., 'oncology', 'immunotherapy', 'GLP-1', 'alzheimer').

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

Filter by recruitment status.

## `crossJoinNihGrants` (type: `boolean`):

Automatically query NIH RePORTER v2 API to attach active federal grant funding ($) and project numbers for trials/sponsors.

## `onlyWithContactEmailOrPhone` (type: `boolean`):

Only return trials with verified direct contact email or phone.

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

Maximum number of cross-joined trial records to return (1 to 5,000).

## Actor input object example

```json
{
  "queryTerm": "oncology",
  "overallStatus": "RECRUITING",
  "crossJoinNihGrants": true,
  "onlyWithContactEmailOrPhone": true,
  "maxItems": 20
}
```

# Actor output Schema

## `results` (type: `string`):

🔗 \[Multi-Source Cross-Joined] Extract recruiting clinical trials from ClinicalTrials.gov v2 + Cross-Join NIH RePORTER grant funding ($) + Harvest ALL multi-center PI direct emails/phones + Compute CRO Patient Recruitment Bottleneck & Site Burden scores.

# 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 = {
    "queryTerm": "oncology",
    "overallStatus": "RECRUITING",
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("grandiose_envelope_0fj/clinical-trials-leads-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queryTerm": "oncology",
    "overallStatus": "RECRUITING",
    "maxItems": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("grandiose_envelope_0fj/clinical-trials-leads-scraper").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 '{
  "queryTerm": "oncology",
  "overallStatus": "RECRUITING",
  "maxItems": 20
}' |
apify call grandiose_envelope_0fj/clinical-trials-leads-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,grandiose_envelope_0fj/clinical-trials-leads-scraper"
        }
    }
}
```

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/AwSyGYXBli8HLY5Rn/builds/wdEYGl3ORyZZQcjrz/openapi.json