Discovery in clinical trials
Gain valuable insights in your clinical research by quickly mining relevant data across various proprietary and public repositories in your role as a pharmaceutical company, clinical trial professional or medical device manufacturer. Leverage semantic technology in combination with AI to extract complex dependencies between adverse events and concomitant medication and more. Model all information using industry standards like MedDRA, SNOMED, CDISC and conform to the highest data protection requirements.
How you’ll benefit
Leverage smart semantic search
- Save time to find required information in complex clinical documentation;
- Uncover hidden insights by effortlessly mining large number of relevant documents (> 500 000 in our use case).
Adopt FAIR data principles
- Improve data interoperability by applying industry-specific standards (WHODrug, LOINC, CDISC);
- Enrich your proprietary terminologies with public reference vocabularies and ontologies.
Aggregate large volumes of information
- Easily manage information across different systems (eTMF, CTMS), proprietary data and public repositories (PubMED) in one central solution;
- Optimize data quality and regulatory compliance by reliably identifying clinical data discrepancies.
Optimize your data analytics workflows
- Increase productivity by introducing custom automatic workflows for document processing;
- Quickly mine highly specific information from clinical study documents and apply the results in context.
How it works
Classify, segment and annotate documents
- Classify, segment and annotate documents with multiple text mining pipelines. Different types of entities are extracted.
- Perform text mining on bullet lists, tables and specific document sections.
Filter & classify
Transform all extracted and generated information into RDF. RDF is resolved and made available to other applications
Analyze & contextualize
Index RDF data in SOLRS by preserving its semantic context. Full text search can be performed using highly efficient indexes.
Semantic search
Integrate data extracted from structured and unstructured sources to extend the knowledge base for improved search and discovery.
Speed up research
Allow users to search for specific terms and related concepts to help them get faster insights.
Why it works
Ontotext’s technology streamlines the process of semantic data integration. By using contextual ontology-based text mining, it makes possible the discovery of relevant content, which remains hidden within raw text.
As a result, we can dramatically reduce the time required to discover the required information. See it in action!
Build and Explore Your Own Knowledge Graph
Drug Dashboards Mash up Information from Many Different Sources
Enrich Knowledge Graphs Using Document Annotation Pipelines
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