# ChEMBL Bioactivity Intelligence (`wakey7dev/chembl-bioactivity-normalizer`) Actor

Query ChEMBL for drug bioactivity data — target interactions, IC50, binding affinity. Drug discovery, pharma R\&D, competitive intelligence.

- **URL**: https://apify.com/wakey7dev/chembl-bioactivity-normalizer.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## 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

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## ChEMBL Bioactivity Intelligence Normalizer

Extract and normalize drug-target bioactivity data from ChEMBL, the world's largest curated database of drug-like molecules and their bioactivities.

### Features

- **Drug/Target Search**: Search by drug name (e.g. 'aspirin', 'imatinib') or target protein (e.g. 'EGFR', 'BRD4')
- **Activity Type Filtering**: Filter by IC50, EC50, Ki, Kd, AC50 values
- **Potency Range**: Filter by activity value in nanomolar (nM) units
- **Normalized Output**: Clean, structured data with standardized drug names, target names, and activity types
- **Rich Metadata**: Includes assay type, organism, confidence scores, and literature references

### Use Cases

- **Pharmaceutical R\&D**: Identify potent compounds for specific targets
- **Drug Repurposing**: Find existing drugs with activity against new targets
- **Competitive Intelligence**: Analyze bioactivity profiles of competitor compounds
- **Academic Research**: Extract training data for ML models predicting drug-target interactions
- **CRO Services**: Screen compound libraries for client projects

### Output Format

Each result includes:

- `moleculeName`: Normalized drug/compound name
- `moleculeChEMBLId`: ChEMBL identifier
- `targetName`: Normalized target protein name
- `targetChEMBLId`: ChEMBL target identifier
- `targetOrganism`: Source organism (e.g. 'Homo sapiens')
- `activityType`: IC50, EC50, Ki, Kd, etc.
- `activityValue`: Numeric value in nM
- `activityUnits`: Units (typically 'nM')
- `assayType`: Binding (B), Functional (F), ADMET (A), etc.
- `confidenceScore`: Target confidence (1-5)
- `pubmedId`: Literature reference (if available)
- `relation`: Activity relationship (=, <, >, ~)

### Pricing

$2.00 per 1,000 bioactivity records returned.

### Example Input

```json
{
  "searchQuery": "EGFR",
  "searchType": "target",
  "activityType": "IC50",
  "maxActivityValue": 100,
  "maxResults": 50
}
```

This returns the 50 most potent IC50 values (< 100 nM) for compounds targeting EGFR.

### Data Source

All data sourced from [ChEMBL](https://www.ebi.ac.uk/chembl/) (EMBL-EBI), licensed under CC BY-SA 3.0.

# Actor input Schema

## `searchQuery` (type: `string`):

Search for a drug name (e.g. 'aspirin', 'imatinib') or target protein (e.g. 'EGFR', 'BRD4')

## `searchType` (type: `string`):

What to search for

## `activityType` (type: `string`):

Filter by activity type (leave empty for all)

## `minActivityValue` (type: `integer`):

Minimum activity value in nanomolar (e.g. 10 for potent compounds)

## `maxActivityValue` (type: `integer`):

Maximum activity value in nanomolar (e.g. 1000 for screening hits)

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

Maximum number of bioactivity records to return

## Actor input object example

```json
{
  "searchQuery": "aspirin",
  "searchType": "molecule",
  "activityType": "",
  "minActivityValue": 0,
  "maxActivityValue": 100000,
  "maxResults": 100
}
```

# Actor output Schema

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

Complete bioactivity dataset with all records

## `summary` (type: `string`):

Human-readable summary of results

## `stats` (type: `string`):

Machine-readable statistics

# 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 = {
    "searchQuery": "aspirin"
};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/chembl-bioactivity-normalizer").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 = { "searchQuery": "aspirin" }

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/chembl-bioactivity-normalizer").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 '{
  "searchQuery": "aspirin"
}' |
apify call wakey7dev/chembl-bioactivity-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wakey7dev/chembl-bioactivity-normalizer"
        }
    }
}

```

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/bTYHfZLVQJtfAm9Ml/builds/GJbmMhDpuJVT5N4eT/openapi.json