Uncover better findings

Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.

Search structured orphan drug and disease information, and integrate it into existing datasets.

Use on- and off-label indications to group drugs together for grouping techniques in ML.

Use target information to build and validate your predictive models.

Adverse Effects

Use known side effects of existing drugs to build and validate your predictive models.

Protein Relationships

Information about bonding to enzyme and protein reactions helps with building and establishing your ML.

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.

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.

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.

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.

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.

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.

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:

Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.

Search structured orphan drug and disease information, and integrate it into existing datasets.

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.

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:

Search eligibility criteria, and abandoned and upcoming drugs from phase one to post-market.

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.

Use on- and off-label indications to group drugs together for grouping techniques in ML.