Uncover
better findings
With the latest drug data at your fingertips
Drug data is rapidly increasing
In size, complexity, and inaccuracy. This is slowing down vital research and leaving us to rely on outdated practices.
Scientific journals
published each year
Of systematic reviews
are inaccurate within
24hrs of publication
Of reviews not
updated in 2 yrs have
incorrect conclusions
All the data you need in one, simple spot
We've built the most comprehensive, up-to-date, & accurate drug database on the market.
Combining the advantages of AI and human expertise, we are able to source, validate, structure, and update our data every day so you don’t have to.
DrugBank is the industry standard for pharmaceutical research
Citations in scientific publications
Spent on research utilizing DrugBank
Top pharma companies are customers
Discover more with our datasets
No matter your research needs, methods, or area of focus, our datasets get you to ‘ah-ha’ — faster.
Machine learning for
Drug Discovery
Quickly integrate deeply connected, machine readable drug data that's been crafted by experts to get you to clinical trial faster.
Popular drug discovery data packages:
Biomedical Knowledge
Complete complex data exploration & analysis with our most comprehensive package
Target Identification
Enhance your analysis with broad information about 17,187 drugs & 19,535 targets
Disease Prioritization
Identify high-potential disease areas to focus your research
Clinical Trials & Rare Disease
Explore deeply curated & connected rare disease trials, treatments, & known targets
Research Landscape
Evaluate prior drug research to determine scientific feasibility & prioritize research
Drug Repurposing
Optimize drug repurposing & predict adverse effects
Precision Medicine
Our data supports algorithms that help you see the whole patient story, such as highlighting risks for disease based on lab analysis, lifestyle, and demographics.
Check out our most requested datasets:
Allergy
Using hypersensitivities and onset times, you can build ML for patients or clinicians to understand risks.
Contraindications
Build algorithms that flag potential contraindications and help clinicians understand risk levels for patients.
Drug-Drug Interactions
Can be used to build ML models that help with decision support and understanding the level of risk when prescribing.
Indications
Use on- and off-label indications to group drugs together for grouping techniques in ML.
Pharmacogenomics
SNP effects and actions are helpful for annotating genetic tests.
Rare Diseases
Search structured orphan drug and disease information, and integrate it into existing datasets.
Machine learning for
Pharmacovigilance
Our ready-to-go machine readable data saves you time and speeds up the creation of predictive algorithms, increasing drug safety and reducing harm.
Check out our most requested datasets:
Adverse Effects
Critical for capturing and reporting possible adverse effects on new or existing drugs.
BlackBox Warnings
Understand Box Warnings for groups of drugs and the risk they can present to patients.
Clinical Trials
Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.
Contraindications
Capture potential contraindications and understand the level of risk for groups of patients.
Cross-Mapping
Map clinical DrugBank data to these codes and associate data from ICD-10, SNOMED, and MedDRA with specific drug information from DrugBank.
Drug-Drug Interactions
Capture known drug-drug or drug-food interactions and build predictive models for potential interactions and risks.
In Silico Testing
Build and validate new tools. Our data is relied on daily, for testing techniques that model pharmacokinetic, pharmacodynamic and toxicology predictions.
Check out our most requested datasets:
Chemical Structure
Use various formats of chemical structures (including SMILES) for your in silico experiments.
Drug Categories
Filter drugs by their chemical structure, taxonomy, and functional groups such as kingdom and class.
Metabolism
Utilize known drug reactions to build models that can predict metabolite reactions for new drugs.
Pharmacology
Leverage existing drug knowledge to forecast possible toxicity, half life, clearance and more for your prospective drugs.
Protein Relationships
Understand and better predict the sequencing of how a protein or enzyme will react.
Targets
Allows you to find or predict underlying causes of potential adverse effects, metabolism, therapeutic activity, and more.
Normalizing & Enhancing
Data Pools & Software
Maintaining and managing data across regions and codes is time consuming and meticulous. Our datasets streamline your work so you can focus on what’s important.
Check out our most requested datasets:
Adverse Effects
Use known adverse effects to better categorize, uncovering new indications, and understand level of risk.
Drug Categories
Help filter drugs by their chemical structure, taxonomy, and functional groups such as kingdom and class.
Indications
Utilize on-label and off-label indications to search, group, and categorize drugs.
Pharmacology
Enhance existing data with known toxicity, pharmacodynamic, pharmacokinetic properties, and predicted ADME.
Targets
Search or group by specific drug-bond and protein relationships.
Therapeutic Categories
Make your data more usable with accurate therapeutic categories based on the FDA's Established Pharmacologic Class.
Business Intelligence
Find new opportunities by examining the most up-to-date drug data, patents, clinical trial information, and much more.
Check out our most requested datasets:
Clinical Trials
Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.
Rare Diseases
Search structured orphan drug and disease information, and integrate it into existing datasets.
Indications
Access approved and prospective on- and off-label indications that are also mapped to clinical trials.
Products by Region
See what new and existing drug products have come to market in various regions.
Targets
Identify existing drug target relations to predict unwanted effects and see areas of opportunity for new discoveries.
Therapeutic Categories
Evaluate and parse groups of drugs by therapeutic class.
Clinical Trial Matching
Quickly analyze trial drug, eligibility criteria, and trial termination reasons.
Check out our most requested datasets:
Clinical Trials
Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.
Rare Diseases
Search structured orphan drug and disease information, and integrate it into existing datasets.
Pharmacology
Enhance existing data with known toxicity, pharmacodynamic, pharmacokinetic properties, and predicted ADME.
Indications
Use on- and off-label indications to group drugs together for grouping techniques in ML.
Explore all of our datasets
From our proprietary drug categories to targets, we have the extensive data you need to power your research.
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