drug-repurposing

Drug Repurposing Pipeline

Systematically evaluate an existing drug for new therapeutic indications by mining evidence across six dimensions: pharmacology, target networks, clinical trials, literature, patents, and safety.

When to Use

• "帮我找 metformin 的新适应症"
• "Sorafenib 除了肝癌还能治什么"
• "Drug repurposing opportunities for thalidomide"
• "X 的老药新用潜力"
• Any query about finding new uses for existing drugs

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Pipeline

Step 1: Drug Profile

Gather comprehensive drug information:

bash: echo "=== DrugBank ===" && \
curl -s "https://go.drugbank.com/unearth/q?searcher=drugs&query=DRUGNAME&button=" 2>/dev/null && \
echo -e "\n=== ChEMBL ===" && \
curl -s "https://www.ebi.ac.uk/chembl/api/data/molecule/search.json?q=DRUGNAME&limit=5" && \
echo -e "\n=== PubChem ===" && \
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/DRUGNAME/JSON"

Extract:

• Approved indications and year of first approval
• Primary mechanism of action
• Known molecular targets (with confidence)
• Chemical class and properties (MW, logP, PSA)
• Half-life, bioavailability, metabolism pathway (CYP enzymes)

Step 2: Target Network Analysis

Map drug targets to disease associations:

bash: echo "=== STRING PPI Network ===" && \
curl -s "https://string-db.org/api/json/network?identifiers=TARGET_GENE&species=9606&required_score=700" && \
echo -e "\n=== OpenTargets Disease Associations ===" && \
curl -s -X POST "https://api.platform.opentargets.org/api/v4/graphql" \
  -H "Content-Type: application/json" \
  -d '{"query":"{ target(ensemblId:\"ENSG_ID\") { id approvedSymbol associatedDiseases(page:{size:20}) { rows { disease { id name } score datatypeScores { componentId score } } } } }"}'

Key analysis:

• Primary targets → known diseases (already approved)
• Secondary/off-targets → new disease candidates
• PPI network neighbors → diseases associated with interacting proteins
• Pathway enrichment → which disease pathways are modulated

Step 3: Clinical Evidence Mining