Clinical Intelligence
Discover the latest trends and historic information about topics of interest such as drug indication, therapy, disease, research activities and more. Our solution provides drug and medical device manufacturers with public and proprietary information merged in a single source-of-truth – a knowledge graph providing actionable insights and local relations between entities from various datasets and documents.
How You’ll Benefit
Easily manage medical data from various sources, such as PubMed and clinicaltrials.gov, in a central intelligence system.
Save valuable time by obtaining relevant information from one interconnected network of knowledge.
Find hidden relationships between entities and trends in medical data.
Increase productivity by introducing custom automatic workflows for document processing.
Improve data interoperability and inexpensively integrate internal data with publicly available open data.
How it Works
Semantic data normalization
- Unlock information locked in silos.
- Ingest any structured data formats – XML, CSV, RDBMS, etc.
- Transform source data models into a unified self-explanatory RDF data model.
- Integrate with NLP pipelines.
Knowledge graph
- Build highly interlinked network of knowledge out of multiple data sources.
- Remove redundancy.
- Apply data validation.
- Maintain data provenance.
Semantic search
- User-friendly Google-like search.
- Concept search and disambiguation.
- Knowledge graph exploration.
- Custom views and Analytical dashboards.
Case Studies
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A Global Pharma Company Uses Ontotext’s Solution for Semantic Similarity Search in Documents
A global Pharma company uses Ontotext’s smart semantic similarity search solution to quickly process large volumes of Regulatory questions and scale up the information extraction.
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Top 10 Pharma Company Uses Ontotext’s Solution for Smarter Search Across Siloed Structured and Unstructured Data
One of the biggest Pharma companies in the world used Ontotext’s solution to build a semantic search tool that would enable its users to easily find relevant information across huge volumes of siloed structured and unstructured data-sources.
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AstraZeneca: Early Hypotheses Testing Through Linked Data
AstraZaneca used Ontotext technology to develop a platform for Interactive Relationship Discovery that enables the identification of long causal relationship chains between the biomedical objects in the Linked Life Data cloud.
Demo service
Discover how to acces and explore high-quality data with Ontotext’s Pharma Regulatory Intelligence Solution.
Products, Solutions and Services Involved
GraphDB
Text Analysis for Content Management
