What biological identifiers does this skill use?

This skill utilizes Ensembl gene IDs for targets, EFO (Experimental Factor Ontology) IDs for diseases, and ChEMBL IDs for drugs to ensure precise data mapping.

Does this skill support custom data queries?

Yes, while it includes helper functions for common tasks, the skill allows for custom GraphQL queries to access the full range of Open Targets data.

Can I use this skill to find drug repurposing opportunities?

Yes, you can identify existing drugs for a disease, explore their mechanisms, and find other targets or indications associated with those compounds.

How should I interpret the association scores?

Scores range from 0 to 1 and represent the relative strength of evidence from various data types. They are ranking metrics rather than absolute probability scores.

Is an API key required to use the Open Targets skill?

No, the Open Targets Platform GraphQL API is public and does not require an API key or authentication for standard programmatic access.

Open Targets Database

Name: Open Targets Database
Author: pur3v4d3r

bypur3v4d3r

•

Data Science & ML

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

About

The Open Targets Database skill provides programmatic access to a massive integration of human genetics, omics, literature, and clinical data for drug discovery. It allows users to search for target-disease associations, evaluate the tractability and safety profiles of specific genes, and analyze the clinical landscape of known drugs. By leveraging the Open Targets GraphQL API, researchers and developers can streamline complex workflows like target prioritization, mechanism-of-action research, and drug repurposing directly within their development environment.

Key Features

Target-disease association scoring based on multi-omic evidence
Searchable drug data including ChEMBL IDs and clinical trial phases
Evidence retrieval from GWAS, literature, and animal models
1 GitHub stars
Detailed gene tractability and safety liability assessments
Custom GraphQL query support for complex scientific data extraction

Use Cases

Conducting competitive intelligence by analyzing the clinical trial status of existing drugs
Assessing the druggability and toxicity risks of candidate genes in early-stage research
Prioritizing therapeutic targets for specific disease indications based on genetic evidence

About

Key Features

Target-disease association scoring based on multi-omic evidence
Searchable drug data including ChEMBL IDs and clinical trial phases
Evidence retrieval from GWAS, literature, and animal models
1 GitHub stars
Detailed gene tractability and safety liability assessments
Custom GraphQL query support for complex scientific data extraction

Use Cases

Conducting competitive intelligence by analyzing the clinical trial status of existing drugs
Assessing the druggability and toxicity risks of candidate genes in early-stage research
Prioritizing therapeutic targets for specific disease indications based on genetic evidence