What types of evidence support the target-disease associations?

Evidence is aggregated from multiple sources including genetic associations, somatic mutations, known drugs, affected pathways, RNA expression, animal models, and literature mining.

Can this skill help with competitive intelligence in pharma?

Yes, it can identify drugs in various clinical trial phases (Phase 1-4) for specific targets or diseases, helping you understand the current clinical landscape.

How should I interpret the association scores?

Scores range from 0 to 1 and indicate the relative strength of evidence. They are ranking metrics based on a harmonic sum of evidence, not absolute probability scores.

Do I need an API key to use the Open Targets skill?

No, the Open Targets Platform GraphQL API is publicly accessible and does not require authentication for the standard queries performed by this skill.

What biological identifiers are used by this skill?

The skill utilizes Ensembl gene IDs for targets (e.g., ENSG00000012048), EFO (Experimental Factor Ontology) IDs for diseases, and ChEMBL IDs for drugs.

Open Targets Database

Name: Open Targets Database
Author: jimmc414

byjimmc414

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324

Data Science & ML

Queries the Open Targets Platform to identify and prioritize therapeutic drug targets using genetic, omic, and clinical evidence.

About

The Open Targets Database skill enables researchers and developers to systematically discover and prioritize therapeutic drug targets by integrating human genetics, omics, literature, and clinical data. It provides programmatic access to the Open Targets Platform's GraphQL API, allowing users to evaluate target tractability, safety liabilities, and disease-target associations with comprehensive evidence scoring. This skill is essential for bioinformatics workflows, target validation, drug repurposing, and competitive intelligence, helping users navigate complex biological datasets to make data-driven decisions in drug discovery.

Key Features

Evaluate target druggability across various modalities like small molecules, antibodies, and PROTACs.
Search disease-target associations with detailed evidence scores from GWAS, ClinVar, and more.
324 GitHub stars
Query comprehensive target annotations including HGNC symbols, tractability, and safety liabilities.
Access drug-specific information such as ChEMBL IDs, synonyms, and withdrawn notices.
Retrieve known drugs for specific diseases including mechanisms of action and clinical trial phases.

Use Cases

Identifying and ranking potential therapeutic targets for complex diseases based on genetic evidence.
Discovering drug repurposing opportunities by analyzing existing indications and cross-referencing mechanisms.
Validating the safety and tractability profile of a gene before initiating drug development.

About

Key Features

Evaluate target druggability across various modalities like small molecules, antibodies, and PROTACs.
Search disease-target associations with detailed evidence scores from GWAS, ClinVar, and more.
324 GitHub stars
Query comprehensive target annotations including HGNC symbols, tractability, and safety liabilities.
Access drug-specific information such as ChEMBL IDs, synonyms, and withdrawn notices.
Retrieve known drugs for specific diseases including mechanisms of action and clinical trial phases.

Use Cases

Identifying and ranking potential therapeutic targets for complex diseases based on genetic evidence.
Discovering drug repurposing opportunities by analyzing existing indications and cross-referencing mechanisms.
Validating the safety and tractability profile of a gene before initiating drug development.