245K nodes. 388K edges. Drug targets, side effects, bioactivity, and adverse events from 5 open sources.
We loaded DrugBank, DGIdb, SIDER, ChEMBL, and OpenFDA into one graph, then asked:
"Which drug has the most reported side effects?"
MATCH (d:Drug)-[:HAS_SIDE_EFFECT]->(se:SideEffect)
RETURN d.name, count(se) AS side_effects
ORDER BY side_effects DESC LIMIT 5| Drug | Side Effects |
|---|---|
| Pregabalin | 839 |
| Duloxetine | 791 |
| Quetiapine | 764 |
| Olanzapine | 738 |
| Aripiprazole | 712 |
One query across five pharmacological databases. Powered by Samyama Graph.
See all 100 benchmark queries →
6 node labels -- Drug, Gene, SideEffect, Indication, Bioactivity, AdverseEvent
5 edge types -- INTERACTS_WITH_GENE, HAS_SIDE_EFFECT, HAS_INDICATION, HAS_ADVERSE_EVENT, BIOACTIVITY_TARGET
5 data sources -- DrugBank (CC0), DGIdb (drug-gene), SIDER (side effects), ChEMBL 36 (bioactivity), OpenFDA FAERS (adverse events)
# Download (8.1 MB)
curl -LO https://github.com/samyama-ai/samyama-graph/releases/download/kg-snapshots-v5/druginteractions.sgsnap
# Start Samyama and import
./target/release/samyama
curl -X POST http://localhost:8080/api/tenants \
-H 'Content-Type: application/json' \
-d '{"id":"druginteractions","name":"Drug Interactions KG"}'
curl -X POST http://localhost:8080/api/tenants/druginteractions/snapshot/import \
-F "[email protected]"git clone https://github.com/samyama-ai/druginteractions-kg.git && cd druginteractions-kg
pip install -e ".[dev]"
python -m etl.download_data --data-dir data
python -m etl.loader --data-dir data --url http://localhost:8080-- Polypharmacy: shared gene targets between two drugs
MATCH (d1:Drug {name: 'Warfarin'})-[:INTERACTS_WITH_GENE]->(g:Gene)
<-[:INTERACTS_WITH_GENE]-(d2:Drug {name: 'Aspirin'})
RETURN g.gene_name AS shared_target
-- Side effects of drugs in Phase 3 clinical trials (cross-KG)
MATCH (d:Drug)-[:HAS_SIDE_EFFECT]->(se:SideEffect)
MATCH (i:Intervention {name: d.name})<-[:TESTS]-(ct:ClinicalTrial)
WHERE ct.phase CONTAINS '3'
RETURN d.name, se.name, ct.nct_idThis KG is one of three biomedical knowledge graphs that together form Samyama's billion-edge benchmark: Clinical Trials (27M edges) + Pathways (835K edges) + Drug Interactions (388K edges), federated with PubMed (1.04B edges).
| Samyama Graph | github.com/samyama-ai/samyama-graph |
| The Book | samyama-ai.github.io/samyama-graph-book |
| Benchmark (100 queries) | Biomedical Benchmark |
| Contact | samyama.dev/contact |
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