DRUG DISCOVERY

Get to market faster

Unify clinical data, scientific research, real world data, and more to accelerate drug discovery.

In pharmaceutical companies, data definitions and schemas can vary significantly from lab to lab, even if those labs are working on related experiments. This can leave researchers operating with incomplete information, which can lead to duplicative efforts and wasted budgets. Stardog provides the highly flexible data layer organizations need to make data findable, accessible, interoperable, and reusable (FAIR) and repeatably identify promising drug targets.

Unify data across labs to identify promising drug targets

Stardog connects all R&D data to let researchers explore the relationships between data in studies, trials, populations, expressions, diseases, and more. Thanks to virtualization, all of this can be done without moving any data between labs. With data unified, researchers can more easily find compounds which create similar effects, see which assays have already been tested, and understand if gene expression could be used as a biomarker.

Learn more:

Watch our webinar on how Knowledge Graphs will transform the pharmaceutical industry.

Scope experiments more efficiently

Scoping new experiments typically requires manual data preparation to gather relevant previous studies and experiments. As a result, researchers are slow to form hypotheses for the basis of experiments, wasting time and resources on inefficient or ill-formed experiments. With Stardog, the full breadth of relevant research, internal and external, is readily available. The Knowledge Graph’s inherent traceability allows researchers to follow their intuition and explore related datasets to help form their hypotheses.

Learn more:

Use SNOMED or other biomedical ontologies to accelerate research

Identify new purposes for previously tested compounds

Help mitigate your costs by repositioning existing drugs. Using similarity search, researchers can find related drug areas in the Knowledge Graph and predict relationships and pathways with ML models trained on the full breadth of available research. Stardog also supports virtualizing large volumes of external research and extracting details via our NLP pipeline, BITES.

  • Quote

    Analysts and biologists ... have the ability follow the chain of custody and talk about the “why” of the data, which is really important.”

    Conrad Leonard, Senior Bioinformatician, QIMR Berghofer

Features

NLP Pipeline

Our NLP pipeline, BITES, allows full-text documents to be combined alongside traditional data sources, enriching the body of data

Data quality management

Stardog’s Data Quality Constraints find inconsistencies across your data silos and flags conflicts

Explainable

Stardog’s query results include full data lineage for easy interpretation and flexible discovery by research scientists

Reusable

Stardog easily incorporates new biomedical data and ontologies into a common data model and language, allowing for easy iterative development across any R&D team