Repurposing hub

Skill BioTender-max/awesome-bio-agent-skills/skills/drugclaw/repurposing_hub

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.

Install

npx -y skills add BioTender-max/awesome-bio-agent-skills --skill repurposing_hub

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Query the Broad Institute Drug Repurposing Hub (~6,800 compounds). Look up drugs by name, gene target, MOA, disease area, Broad ID, or InChIKey. Returns clinical phase, mechanism of action, targets, disease area, indication, and chemical identifiers.

SKILL.md

2.6 KB, as published. Nobody here has run it

Drug Repurposing Hub Query Skill

Search the Broad Institute Drug Repurposing Hub by any entity. Auto-detects input type by pattern:

Input Pattern	Detected As	Match Logic
`BRD-A12345678`	Broad compound ID	prefix on `broad_id`
`ABCDEFGHIJKLMN-OPQRSTUVWX-Y`	InChIKey	exact on `InChIKey`
`EGFR`, `BRAF`, `TOP1`	Gene / target	exact token in `target` (pipe-separated)
anything else	free text	substring on `pert_iname`, `moa`, `indication`, `disease_area`

API

Function	Input	Returns
`load_drugs(path)`	drug TSV path	list[dict]
`load_samples(path)`	sample TSV path	list[dict]
`load_merged()`	—	list[dict] (drugs + chemical IDs from samples)
`search(entity)`	single entity string	list[dict]
`search_batch(entities)`	list of entity strings	dict[str, list[dict]]
`summarize(hits, entity)`	hits + label	compact LLM-readable text
`to_json(hits)`	list[dict]	list[dict] (JSON-serialisable)

Usage

See if __name__ == "__main__" block in 29_Drug_Repurposing_Hub.py for runnable examples covering: drug name, gene target, MOA keyword, disease area, batch search, and JSON output.

from importlib.machinery import SourceFileLoader
hub = SourceFileLoader("hub", "29_Drug_Repurposing_Hub.py").load_module()

# Single drug lookup
hits = hub.search("imatinib")
print(hub.summarize(hits, "imatinib"))

# Target-based search
hits = hub.search("EGFR")

# Batch
results = hub.search_batch(["metformin", "aspirin", "BRAF"])

Data

Source: Broad Institute Drug Repurposing Hub (https://repo-hub.broadinstitute.org/repurposing)
Drug file: repo-drug-annotation-20200324.txt — tab-delimited, !-prefixed comment lines
- Columns: pert_iname, clinical_phase, moa, target, disease_area, indication
Sample file: repo-sample-annotation-20240610.txt — tab-delimited, !-prefixed comment lines
- Columns include: broad_id, pert_iname, InChIKey, pubchem_cid, smiles, vendor, purity, etc.
Merge: on pert_iname; first sample with non-empty InChIKey is kept per drug
Path: DATA_DIR variable in 29_Drug_Repurposing_Hub.py
Citation: Corsello SM et al. Nature Medicine 23, 405–408 (2017). doi:10.1038/nm.4306