# Clinical Trials Protocol & Fast-Track Approvals Tracker (`papa_developers/clinical-trials-approvals-scraper`) Actor

Extracts, structures, and standardizes global biotech & pharma clinical trials, FDA/EMA phase transitions, breakthrough therapy / fast-track designations, study endpoints, and sponsor intelligence.

- **URL**: https://apify.com/papa\_developers/clinical-trials-approvals-scraper.md
- **Developed by:** [Hunny](https://apify.com/papa_developers) (community)
- **Categories:**
- **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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Clinical Trials Protocol & Fast-Track Approvals Tracker

> Real-time intelligence and data extraction stream monitoring global biotechnology and pharmaceutical clinical trials, FDA/EMA phase transitions, breakthrough therapy & fast-track designations, and primary endpoint readout calendars.

### Features

- **Global Registry Integration**: Standardizes interventional study protocols and Phase 1–3 pivotal trials across ClinicalTrials.gov (NCT) and European Union Clinical Trials (EU CT).
- **Regulatory Fast-Track Intelligence**: Tracks expedited regulatory statuses including FDA Breakthrough Therapy, Fast Track, Accelerated Approval pathways, and Orphan Drug designations.
- **Deep Clinical Metadata**: Structured extraction of lead molecules, mechanisms of action, patient enrollment targets, primary completion dates, and primary efficacy endpoints.
- **Pay-Per-Event Monetization**: Predictable micro-billing ($0.005 per extracted record) via the Apify Store Pay-Per-Event pricing model.

### Pricing (Pay-Per-Event)

- **$0.005 USD per extracted clinical trial record**
- Billed dynamically via Apify Pay-Per-Event pricing model.

### Input Parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `phases` | Array | `["all"]` | Trial phases: `phase-1`, `phase-2`, `phase-3`, `phase-4`, `early-phase-1` |
| `condition_filter` | String | `"all"` | Area: `oncology`, `neurology`, `rare-diseases`, `immunology`, `cardiovascular` |
| `fda_designation` | String | `"all"` | Designation: `fast-track`, `breakthrough-therapy`, `accelerated-approval`, `orphan-drug` |
| `status_filter` | String | `"all"` | Recruitment status: `recruiting`, `active-not-recruiting`, `completed` |
| `min_enrollment` | Integer | `0` | Minimum cohort enrollment threshold |
| `max_records` | Integer | `50` | Maximum trial records to export (1 to 500) |

### Output Format

Each clinical trial record contains:

```json
{
  "nct_id": "NCT05912481",
  "study_title": "A Phase 3, Randomized, Double-Blind Study of mRNA-4157 (V940) in Combination With Pembrolizumab...",
  "sponsor": "ModernaTX, Inc.",
  "collaborators": ["Merck Sharp & Dohme LLC"],
  "phase": "phase-3",
  "condition": "oncology",
  "primary_intervention": "mRNA-4157 (V940) individualized neoantigen therapy + Pembrolizumab",
  "study_type": "Interventional",
  "study_status": "recruiting",
  "enrollment_target": 1089,
  "fda_designation": "breakthrough-therapy",
  "primary_completion_date": "2029-07",
  "primary_outcome_measure": "Recurrence-Free Survival (RFS) assessed by investigator",
  "registry_url": "https://clinicaltrials.gov/study/NCT05912481",
  "summary": "Pivotal global Phase 3 evaluating individualized mRNA cancer vaccine...",
  "scraped_at": "2026-09-04T14:15:00+00:00"
}
```

### Python Integration Example

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

run_input = {
    "phases": ["phase-3"],
    "condition_filter": "oncology",
    "fda_designation": "breakthrough-therapy",
    "max_records": 50
}

run = client.actor("papa_developers/clinical-trials-approvals-scraper").call(run_input=run_input)

for item in client.dataset(run.default_dataset_id).iterate_items():
    print(f"[{item['nct_id']}] {item['sponsor']} - {item['primary_intervention']} (Completion: {item['primary_completion_date']})")
```

### License

Apache-2.0

# Actor input Schema

## `phases` (type: `array`):

Select trial phases to extract.

## `condition_filter` (type: `string`):

Filter by primary disease indication.

## `fda_designation` (type: `string`):

Filter by FDA/EMA expedited regulatory status.

## `status_filter` (type: `string`):

Filter by trial progression status.

## `min_enrollment` (type: `integer`):

Filter trials with patient cohort size greater than or equal to this threshold.

## `max_records` (type: `integer`):

Maximum number of clinical trial records to export.

## Actor input object example

```json
{
  "phases": [
    "all"
  ],
  "condition_filter": "all",
  "fda_designation": "all",
  "status_filter": "all",
  "min_enrollment": 0,
  "max_records": 50
}
```

# Actor output Schema

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

Structured clinical trials protocols and approval records in default dataset

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("papa_developers/clinical-trials-approvals-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("papa_developers/clinical-trials-approvals-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 '{}' |
apify call papa_developers/clinical-trials-approvals-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,papa_developers/clinical-trials-approvals-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/VjAOHXlGeBH3EyI4F/builds/l4vkHWiezVef7fsCW/openapi.json