Knowledge Graph Applications

We specialize in developing knowledge graph applications, seamlessly integrating public and proprietary data into a Neo4j graph database.

This represents your organization's collective intelligence. On this platform, we build efficient tools for data management, visualization, and thorough analysis. Our goal is to transform your complex data into useful, actionable insights.

Health Data Harmonization

We aid in the standardization of health data to widely recognized formats like FHIR and OMOP CDM.

Our comprehensive service includes strategic data planning, vocabulary mapping, and ETL process design.

We cater to your unique needs by implementing bespoke ETL solutions based on your specific data and infrastructure setup.

Workshops

In our comprehensive workshops, we focus on equipping participants with the knowledge needed to helm successful Neo4j projects within the life sciences sector.

Our curriculum spans the entirety of the development process, from making informed decisions, crafting effective data models, to the final creation of robust graph applications.

We provide the tools and understanding necessary to fully harness the power of Neo4j.

Data Strategy

We collaborate with you to devise a data-driven strategy, designed to extract maximum value from your data assets.

Using knowledge graphs and data harmonization standards, we fuse internal and public data sources, unearthing untapped opportunities.

Our strategic approach not only refines existing processes but also identifies potential for innovative business models.

Real World Evidence

We utilize Real-World Evidence (RWE) to enhance research across the drug development lifecycle. With knowledge graphs and data harmonization, we identify unmet needs in RWE and integrate it with proprietary molecule libraries, disease pathways, and drug targets.

Multi Omics

Leveraging knowledge graphs, we aid in identifying targets within multi-omics intersections. We structure heterogeneous data by annotating pathways and diseases. Graph algorithms like clustering and community detection enhance your data analysis, enriching your research context.

Publications & Patents

Valuable insights often lie hidden in unstructured text. We employ natural language processing to mine pertinent data points from textual sources. These insights are integrated into a knowledge graph, blending seamlessly with other internal and external data.