- Date 23 Sep 2013
- Sectors Life Sciences
I2E 4.1 opens up new opportunities for connecting actionable insights from unstructured data across diverse cloud and enterprise-based content silos
I2E’s new Linked Server functionality facilitates easier access to text mining across different content silos wherever they might be located, whether in-house data or content served from the cloud, including from Linguamatics’ own I2E OnDemand platform. This federated approach will enable faster linking of extracted information from diverse unstructured data sources such as scientific literature, clinical data, patents and in-house information, leading to increased speed to insight.
Amongst other product enhancements, index optimization delivers reductions in index sizes of around 30%, leading to savings in storage costs. This is particularly significant as customers scale up their enterprise text mining operations to deal with the challenges of big data.
“This is an exciting time for Linguamatics”, commented John M Brimacombe, Executive Chairman of Linguamatics. “Our latest release opens up opportunities for our customers to improve their access to big data and further increase their speed to insight, decision making and competitive advantage. Through continual innovation we are responding to a customer base working with demanding, sophisticated unstructured data requirements. Linguamatics is setting the standard in agile, NLP-based text mining.”
Linguamatics is the world-leader in deploying innovative natural language processing (NLP)-based text mining for high-value knowledge discovery and decision support. Linguamatics I2E is used by top commercial, academic and government organizations, including nine of the top ten global pharmaceutical companies and the US FDA. I2E can be used to mine a wide variety of text resources, such as scientific literature, patents, clinical trials data, news feeds and proprietary content. It is available as an in-house enterprise system and software-as-a-service (SaaS) on the cloud.
Typical applications in pharmaceuticals, biotechnology, government and healthcare include:
- Mapping gene-disease relationships and identifying potentially novel therapeutic targets
- Biomarker discovery
- Drug repurposing
- Drug safety
- Patent analysis
- Clinical trial site selection and study design
- Mining electronic health records to improve prediction of health outcomes
- Translational medicine
- Competitive intelligence
Business intelligence applications include social media mining and sentiment analysis.