# PubMed Biomedical & Clinical Research Scraper (`litezero/pubmed-medical-research-scraper`) Actor

Extract 36M+ biomedical research papers, clinical trial citations, journal abstracts, medical authors, and DOI links from PubMed NCBI.

- **URL**: https://apify.com/litezero/pubmed-medical-research-scraper.md
- **Developed by:** [LiteZero](https://apify.com/litezero) (community)
- **Categories:** Developer tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.84 / 1,000 item scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## 🧬 PubMed Biomedical & Clinical Research Scraper

Search and extract 36M+ peer-reviewed biomedical papers, clinical trials, medical journal citations, author affiliations, and DOI links directly from **PubMed (NCBI / National Library of Medicine)**.

***

### 🥊 Why This Actor Beats the Competition

| Feature | ⚡ PubMed Research Scraper | 🐢 Traditional Web Crawlers |
|---|---|---|
| **Speed** | **30+ citations in < 2 seconds** | Slow DOM pagination across legacy NIH portals |
| **Pricing** | **$1.20 / 1,000 items** (Platform Usage: FREE) | High institutional database subscription fees |
| **Comprehensive Data** | DOIs, PubMed Central (PMC) links, journals, authors | Often misses digital object identifiers & open access links |
| **Direct Full Text** | Links directly to PMC free full-text & publisher DOIs | Requires manual citation tracking |
| **Anti-Bot Blocking** | Official NCBI E-utilities integration | Captcha challenges on third-party aggregators |

***

### 🛠️ Step-by-Step: How to Use

#### Method 1: Apify Web Console (No-Code GUI)

1. Enter your target **Medical Topic / Search Query** (e.g. `crispr cas9`, `artificial intelligence radiology`, `car-t immunotherapy`).
2. Set **Max Items** and click **Start**.
3. Download structured medical citation datasets in JSON, CSV, or Excel.

#### Method 2: Python SDK

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
    "searchTerm": "mRNA vaccines oncology",
    "maxItems": 25
}
run = client.actor("litezero/pubmed-medical-research-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"PMID {item['pmid']}: {item['title']} ({item['journal']}, {item['pubDate']})")
```

#### Method 3: Node.js SDK

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('litezero/pubmed-medical-research-scraper').call({
    searchTerm: 'deep learning ophthalmology',
    maxItems: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Extracted ${items.length} PubMed articles.`);
```

#### Method 4: REST API / cURL

```bash
curl "https://api.apify.com/v2/acts/litezero~pubmed-medical-research-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerm": "glp-1 receptor agonists", "maxItems": 20}'
```

***

### 📥 Input Parameters

| Field | Type | Default | Description |
|---|---|---|---|
| `searchTerm` | String | `"artificial intelligence radiology"` | Biomedical keyword, medical topic, disease, or drug name to search. |
| `maxItems` | Integer | `30` | Maximum number of research articles to extract. |

***

### 📤 Output Data Dictionary

```json
{
  "pmid": "38459201",
  "title": "Artificial intelligence in clinical radiology: practical implementation and future frontiers",
  "journal": "Radiology",
  "pubDate": "2024 Mar",
  "volume": "310",
  "issue": "3",
  "pages": "e231920",
  "authors": [
    "Smith J",
    "Johnson K",
    "Williams E"
  ],
  "doi": "10.1148/radiol.231920",
  "pubmedCentralId": "PMC10928374",
  "doiUrl": "https://doi.org/10.1148/radiol.231920",
  "pubmedUrl": "https://pubmed.ncbi.nlm.nih.gov/38459201/",
  "scrapedAt": "2026-10-04T10:00:00.000Z"
}
```

***

### 💡 Top Use Cases

1. **Biotech & Pharma Competitive Intelligence:** Track breakthrough clinical findings, drug mechanisms, and therapeutic trials in real time.
2. **Medical AI & RAG Knowledge Bases:** Ingest validated biomedical research citations and abstracts into healthcare LLM applications.
3. **Academic Meta-Analyses & Systematic Reviews:** Automate literature screening across millions of peer-reviewed journals.

# Actor input Schema

## `searchTerm` (type: `string`):

Biomedical topic, drug name, disease, or medical keyword (e.g. 'crispr cas9', 'artificial intelligence radiology', 'mrna vaccine').

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

Maximum number of research articles to extract.

## Actor input object example

```json
{
  "searchTerm": "artificial intelligence radiology",
  "maxItems": 30
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("litezero/pubmed-medical-research-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("litezero/pubmed-medical-research-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 litezero/pubmed-medical-research-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,litezero/pubmed-medical-research-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/oDtwlQbbpr72Cat8o/builds/eSWhqkxzM7blAF7aQ/openapi.json