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opentargets-database

Query Open Targets Platform for disease–target associations and therapeutic candidates.

783|65|Updated Feb 27, 2026
Search Tags:#graphql#drug discovery#opentargets#disease association#evidence retrieval#target prioritization#genetics and omics
One-click install
npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill opentargets-database-leonchaox
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: opentargets-database
Source: https://github.com/LeonChaoX/qinyan-academic-skills/tree/main/skills/12-%E7%A7%91%E5%AD%A6%E6%95%B0%E6%8D%AE%E5%BA%93/opentargets-database
Command: npx skills add https://github.com/LeonChaoX/qinyan-academic-skills --skill opentargets-database-leonchaox

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

It helps researchers rapidly identify and prioritize therapeutic targets for a disease by consolidating human genetics, tractability, safety liabilities, and known drug evidence in one place.

Core Features & Use Cases

  • Target-disease association discovery: Retrieve ranked target–disease links with evidence breakdown and scores for hypothesis building.
  • Target prioritization & diligence: Pull tractability (modality), safety liabilities, and genetic constraint signals to assess druggability and risk.
  • Mechanism and repurposing intelligence: Get known drugs for an indication and retrieve drug mechanisms, clinical trial phases, and adverse-event related context when available.

Use case: You are screening candidate genes for a cancer or rare disease topic and need evidence-backed prioritization plus existing therapeutic precedent to decide what to test next.

Quick Start

Use the skill to query Open Targets for known drugs and target-disease evidence for a specific disease ID you provide (EFO format) and return the top ranked associations with evidence type scores.

Frequently Asked Questions about opentargets-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find disease-target associations and therapeutic target candidates with supporting evidence?▼

To find disease-target associations, you query the Open Targets Platform via GraphQL using disease identifiers (EFO IDs) and target identifiers (Ensembl IDs). This retrieves ranked disease-target links and evidence records.

How can I assess target prioritization and druggability for candidate genes?▼

You can assess target prioritization by retrieving tractability, safety liabilities, and genetic constraint signals via GraphQL queries. This provides evidence-backed data on druggability and risk for your candidate genes.

Can I retrieve known drugs and repurposing intelligence for a specific disease using GraphQL?▼

Yes, you can retrieve known drugs and repurposing intelligence by querying the Open Targets Platform with disease EFO IDs and drug ChEMBL IDs. This returns drug mechanisms, clinical trial phases, and adverse event context.

What identifiers do I need to query Open Targets for drug discovery and evidence retrieval?▼

You need Ensembl IDs for targets, EFO IDs for diseases, and ChEMBL IDs for drugs. These programmatic GraphQL identifiers are required to return structured association, tractability, and safety records.

Does the Open Targets database support target prioritization for rare diseases and cancer screens?▼

Yes, Open Targets supports target prioritization for rare diseases and cancer screens by consolidating human genetics, tractability, and safety liabilities to help you decide what to test next.

What are the limitations of using GraphQL for Open Targets evidence retrieval?▼

A limitation of GraphQL evidence retrieval is the strict requirement for specific programmatic identifiers like Ensembl, EFO, and ChEMBL IDs. Queries will fail without these exact inputs.

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