Linked Data Integration for Pharma

Ontotext Pharma Insights helps you:

Combine structured and unstructured analytical queries

A single interface unites your data stores.

Increase the accuracy of information mining

Precise document sectioning yields accurate results.

Retrieve complex entities

Adverse events, bio markers or lab results can be searched using standardized terminologies.

Combine structured and unstructured analytical queries

A single interface unites your data stores.

Create comprehensive queries

Include both public data and your own data in search results.

Improve drug development through better information access

Ontotext Pharma Insights is a unified document analysis solution that helps you quickly and easily find the information you need to speed drug development. It blends document structure analysis with text mining and semantic data integration.

Our algorithm for document structure analysis provides the proper context for search terms. For example users can determine if “diabetes” was a reason (indication and inclusion criteria) or an outcome (adverse event) of a trial. It supports the extraction of complex relationships like drug dosing, adverse events reports from tables and much more. All extracted information is modeled using standard public or internal terminology systems like MedDRA, SNOMED, LOINC, CDISC. 

Features

Semantic Search

Benefits

  • Save time locating study information
  • Retrieve accurate, relevant results
  • Reduce the time required to understand the complete clinical study in context

Information Aggregation

  • Identify contradicting or missing Information
  • Improve the quality of the answers

Standardized Terminology

  • Easier data interoperability and collaboration across teams
  • Improve communication using company approved terminology standards

Custom Search Grammars

  • Quickly mine highly specific information from clinical study documents
  • Apply the results in context.

Main components of Pharma Insights

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.

Transform all extracted and generated information into RDF. RDF is resolved and made available to other applications.

Classify,-segment-and-annotate-documents

Filter & Classify

Transform all extracted and generated information into RDF. RDF is resolved and made available to other applications

Filter&Classify

Analyze & Contextualize

Index RDF data in SOLRS by preserving its semantic context. Full text search can be performed using highly efficient indexes.

Analyze&Contextualize

Semantic Search

Integrate data extracted from structured and unstructured sources to extend the knowledge base for improved search and discovery.

Semantic-Search

Speed Up research

Allow users to search for specific terms and related concepts to speed up research.

Speed-Up-Research

Pharma Insights in action

Pharma Insights streamlines the process of semantic data integration. Using contextual ontology-based text mining it makes possible the discovery of relevant content, which remains hidden within unstructured texts.

As a result Pharma Insights dramatically reduces the time required to discover the required information. See how Pharma Insights works in action!

Build and Explore Your Own Linked Life Data Cloud

Pharma Insights can integrate both public and proprietary data into a highly interconnected linked data network. The system uses both semantic instance mappings and advanced information extraction pipelines to identify all semantically related objects among different data sources. As a result, Ontotext Insights Platform creates huge network of semantically interconnected biomedical objects, which could be easily explored using simplified faceted type search interface or just browsing through the objects in the linked data network. The current vide explains how the linked life data is build and how the data can be explored.

Drug Dashboards mash up Information from many different sources

In this video we will demonstrate how using Pharma Insights, we can build comprehensive dashboards, which describe in details a particular category of information. Drug Dashboards mash up information from many different sources and represent it with interactive visualization widgets. One of the most important parts of Pharma Insights is the Drug Dashboard, which integrates information from many public drug data sources like DrugBank and drugs At FDA with clinical study data from Clinical Trials.gov and Drug Product Brochures from DailyMed.

Generate Linked Data using the Document Annotation Pipelines

Pharma Insights uses advanced information extraction pipelines which are able to categorize documents, recognize semantic sections and semantically annotate content with wide range of biomedical concept types. Due to the contextualization of the semantic annotations, Pharma Insights Platform is able to model the extracted knowledge into RDF, which is loaded back in the semantic repository and fused with the structured data already integrated into highly interconnected linked data cloud of biomedical information. The information extraction pipelines are automated and could process from a single file or web page to a batch of documents. At the same time, Pharma Insights Platform, allows manual validation and correction by the end user at any step within the process. This guarantees absolute control and high quality of the generated data that is usually recognized as the main weakness of mass annotation services.

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