Data source
Data from DrugBank, delivered clean.
2 datasets pulled from DrugBank's releases, checked field by field and shipped the way you want them — daily, weekly, or hourly, your call.
- 2 datasets
- 2 industrys
- Real rows on request
Biotechnology
1DrugBank Online
Pharmaceuticals
1DrugBank Open Data (standard catalog data)
Pick a catch, see the rows.
Name any DrugBank dataset and we send real rows from it — not a screenshot of rows. 1,744 datasets. Pick your catch.
Get a sampleAPI, files, or your warehouse. Daily, weekly, or hourly.
Straight answers about DrugBank data
What does Datadory deliver from the DrugBank source?
Two drug-knowledgebase datasets shipped as named deliverables. DrugBank Online contributes the pharmacology: one record per drug with indication text, mechanism of action, ATC codes, group membership and linked target, enzyme, carrier and transporter proteins. DrugBank Open Data (standard catalog data) contributes the identity layer: canonical accessions, names, synonyms, SMILES and InChI keys built to make every downstream system agree on which molecule it is looking at.
How many drugs do the DrugBank datasets cover?
The knowledgebase spans drug groups covering approved, experimental, nutraceutical, illicit, withdrawn and investigational drugs, organized across ATC classifications, pathways, targets and pharmaco-omics categories; the identity subset pairs the same accession namespace with structures. Entry counts ride on each release rather than being fixed here, so your sample reflects the current release exactly as delivered.
Can I join DrugBank data to my own compound or product list?
That is the designed use of the pair. Canonical DrugBank accessions act as the join key, synonyms absorb brand-name and research-code variation, and InChI keys settle identity by structure rather than spelling. External-identifier bridges toward ChEBI, ChEMBL and PubChem extend the same joins outward, so a vendor list, a claims file or an internal compound registry resolves onto one canonical spine.
Does the data distinguish approved drugs from investigational ones?
Yes. A groups enum rides on every knowledgebase record - approved, investigational, experimental, nutraceutical, illicit, withdrawn, vet_approved - which makes regulatory posture a filterable column rather than a footnote. Pair it with ATC codes and you can read who holds approved territory versus investigational ground inside a therapeutic class in one query.