drug-discovery-search

End-to-end drug discovery platform combining ChEMBL compounds, DrugBank, targets, and FDA labels. Natural language powered by Valyu.

42 stars

Best use case

drug-discovery-search is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

End-to-end drug discovery platform combining ChEMBL compounds, DrugBank, targets, and FDA labels. Natural language powered by Valyu.

Teams using drug-discovery-search should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/drug-discovery-search/SKILL.md --create-dirs "https://raw.githubusercontent.com/Zaoqu-Liu/ScienceClaw/main/skills/drug-discovery-search/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/drug-discovery-search/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How drug-discovery-search Compares

Feature / Agentdrug-discovery-searchStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

End-to-end drug discovery platform combining ChEMBL compounds, DrugBank, targets, and FDA labels. Natural language powered by Valyu.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Drug Discovery Search

Search across all major drug discovery databases (ChEMBL, DrugBank, FDA drug labels, Open Targets) simultaneously using natural language queries powered by Valyu's semantic search API.

## Why This Skill is Powerful

- **No API Parameter Parsing**: Just pass natural language queries directly - no need to construct complex search parameters
- **Semantic Search**: Understands the meaning of your query, not just keyword matching
- **Full-Text Access**: Returns complete compound, target, and drug information
- **Image Links**: Includes molecular structures and data visualizations
- **Comprehensive Coverage**: Search across ChEMBL, DrugBank, drug labels, and Open Targets simultaneously
- **Unified Results**: Get results from all drug discovery sources in a single query

## Requirements

1. Node.js 18+ (uses built-in fetch)
2. Valyu API key from https://platform.valyu.ai ($10 free credits)

## CRITICAL: Script Path Resolution

The `scripts/search` commands in this documentation are relative to this skill's installation directory.

Before running any command, locate the script using:

```bash
DRUG_DISCOVERY_SCRIPT=$(find ~/.claude/plugins/cache -name "search" -path "*/drug-discovery-search/*/scripts/*" -type f 2>/dev/null | head -1)
```

Then use the full path for all commands:
```bash
$DRUG_DISCOVERY_SCRIPT "JAK2 inhibitors" 20
```

## API Key Setup Flow

When you run a search and receive `"setup_required": true`, follow this flow:

1. **Ask the user for their API key:**
   "To search drug discovery databases, I need your Valyu API key. Get one free ($10 credits) at https://platform.valyu.ai"

2. **Once the user provides the key, run:**
   ```bash
   scripts/search setup <api-key>
   ```

3. **Retry the original search.**

## When to Use This Skill

- End-to-end drug discovery information
- Target validation through compounds and trials
- Complete drug development information
- Compound optimization with target data
- Safety and efficacy research
## Output Format

```json
{
  "success": true,
  "type": "drug_discovery_search",
  "query": "JAK2 inhibitors",
  "result_count": 20,
  "results": [
    {
      "title": "Compound/Drug/Target Title",
      "url": "https://...",
      "content": "Full data including compounds, targets, mechanisms...",
      "source": "chembl|drugbank|drug-labels|open-targets",
      "relevance_score": 0.95,
      "images": ["https://example.com/structure.png"]
    }
  ],
  "cost": 0.035
}
```

## Processing Results

### With jq

```bash
# Get titles
scripts/search "query" 20 | jq -r '.results[].title'

# Get URLs
scripts/search "query" 20 | jq -r '.results[].url'

# Extract full content
scripts/search "query" 20 | jq -r '.results[].content'

# Filter by source
scripts/search "query" 20 | jq -r '.results[] | select(.source == "chembl") | .title'
```

## Common Use Cases

### Target Identification

```bash
# Find validated targets and compounds
scripts/search "BTK inhibitors for autoimmune diseases" 50
```

### Lead Optimization

```bash
# Search SAR and compound data
scripts/search "EGFR inhibitors blood-brain barrier penetration" 40
```

### Drug Repurposing

```bash
# Find repurposing opportunities
scripts/search "mTOR inhibitors cancer and aging" 30
```

### Safety Assessment

```bash
# Gather safety and interaction data
scripts/search "tyrosine kinase inhibitors cardiac toxicity" 60
```


## Error Handling

All commands return JSON with `success` field:

```json
{
  "success": false,
  "error": "Error message"
}
```

Exit codes:
- `0` - Success
- `1` - Error (check JSON for details)

## API Endpoint

- Base URL: `https://api.valyu.ai/v1`
- Endpoint: `/search`
- Authentication: X-API-Key header

## Architecture

```
scripts/
├── search          # Bash wrapper
└── search.mjs      # Node.js CLI
```

Direct API calls using Node.js built-in `fetch()`, zero external dependencies.

## Adding to Your Project

If you're building an AI project and want to integrate Drug Discovery Search directly into your application, use the Valyu SDK:

### Python Integration

```python
from valyu import Valyu

client = Valyu(api_key="your-api-key")

response = client.search(
    query="your search query here",
    included_sources=["valyu/valyu-chembl", "valyu/valyu-drugbank", "valyu/valyu-drug-labels", "valyu/valyu-open-targets"],
    max_results=20
)

for result in response["results"]:
    print(f"Title: {result['title']}")
    print(f"URL: {result['url']}")
    print(f"Content: {result['content'][:500]}...")
```

### TypeScript Integration

```typescript
import { Valyu } from "valyu-js";

const client = new Valyu("your-api-key");

const response = await client.search({
  query: "your search query here",
  includedSources: ["valyu/valyu-chembl", "valyu/valyu-drugbank", "valyu/valyu-drug-labels", "valyu/valyu-open-targets"],
  maxResults: 20
});

response.results.forEach((result) => {
  console.log(`Title: ${result.title}`);
  console.log(`URL: ${result.url}`);
  console.log(`Content: ${result.content.substring(0, 500)}...`);
});
```

See the [Valyu docs](https://docs.valyu.ai) for full integration examples and SDK reference.

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