Identify new repurposing opportunities
with DrugBank data

Our Drug-Protein Relationships dataset provides valuable information for drug repurposing, such as targets, enzymes, carriers, and transporters. Off-target interactions, and annotations describing pharmacological action, type of interaction (antagonist, agonist, substrate, inhibitor, and inducer), and protein and gene identifiers/sequences, are also included in the Drug-Protein Relationships dataset. This dataset includes over 17,000 unique references, providing our customers with excellent information to investigate off-target relationships, and enrich their experimental data to quickly identify drug repurposing candidates.

Customers interested in drug repurposing can use our approved and clinical trial indications data to improve their research outcomes, train machine-learning models, or repurpose failed clinical trials. The indications dataset includes approved indications, most common off-label indications, and clinical trial indications. The indications are linked to MedDRA and ICD10 to facilitate data integrations.

The side effects dataset includes information collected from clinical trial data, drug labels, and post-market reporting and includes incidence rates when available. Each listing includes the name of the condition, synonyms for the condition, and associated ICD10 or MedDRA identifiers. Customers have used this dataset to compare side effects, and discover drugs with similar off-target effects to identify potential drug repurposing candidates.

Our customers use network-based approaches to identify repurposing opportunities, as well as enrich their GWAS and omics datasets to identify new patterns within the datasets. To aid in this, our pathways and metabolic reactions datasets provide structured descriptions of every step in the metabolism of a drug. This includes the enzymes involved and the chemical structures of every metabolite. Detailed drug and disease pathways can reinforce existing datasets or provide new data insights for companies. By using our pathway data, users can investigate downstream effects to identify potential mechanisms.

Our customers are able to identify potential adverse effects when completing drug repurposing research by using our datasets. We collect data from clinical trials, drug labels, and post-market reporting, and include incidence rates when available. Each listing includes the name of the condition, and associated ICD10 and MedDRA identifiers. The datasets can be used to compare side effects, identify similar drugs, identify off-target effects and review failed trials.

Identify the potential toxicity of a chemical or drug structure using our Drug Toxicity Data. Our customers use this data in specific drug repurposing cases, as well as in the development of precision medicine treatments, and tailored disease treatments.

Our customers have access to over 1.3 million accurate, updated, detailed drug-drug interactions covering all FDA and Health Canada approved drugs, sourced from drug labels, clinical guidelines and references, to use in their research and technology development.

DrugBank offers robust drug metabolism data, including metabolism reactions associated with 110 enzymes, and route of elimination. The data includes the type of reaction, the enzymes and other proteins involved and the name and structure of the drug metabolites. DrugBank customers use this data in drug discovery, repurposing, and in their AI solutions.