SciBite and PerkinElmer provide advanced analytics from unstructured scientific data

PerkinElmer, Inc., a global leader committed to innovating for a healthier world, today announced enhancements to the PerkinElmer Signals™ Perspectives platform, powered by SciBite and Attivio^®. The platform will provide life sciences and environmental researchers advanced text analytics and semantic understanding of their unstructured data. Scientists and business analysts can rapidly identify and use the relevant data to help answer complex analytical queries by leveraging the visual capabilities of TIBCO Spotfire^®.

Researchers struggle to derive insights from their unstructured data. Starting from a wide range of disparate data sources including free text, they must have analytics solutions that can understand the semantics of their data. To meet this challenge, SciBite ontologies contain tens of millions of scientific terms across many life sciences topics including toxicology, clinical development, and intellectual property – helping to eliminate a major bottleneck in analyzing text.

These capabilities enable PerkinElmer’s customers to perform advanced text analytics on unstructured data sources such as scientific literature. They can also enhance their clinical data review process with Real World Evidence, and improved hospital operations by unlocking the value in free text electronic medical records, safety- and procedure reports, claims, and other similar data sets.

How it works

The PerkinElmer Signals platform provides on-demand access to high-volume screening, clinical, research, and other structured and unstructured data sources. SciBite extends the content analytics capabilities for enhanced text mining. Alongside the Attivio Active Intelligence Engine, content is aggregated from structured, semi-structured and unstructured sources, both in-house and public. The data is structured, summarized, enriched, and unified for immediate use in analysis.

Data analysts and scientists can selectively obtain related information from the broader universe that relates to their areas of interest. The TIBCO Spotfire software then investigates and analyzes the data, generating visually intuitive, interactive displays to support collaboration and decision making. Data is enriched through dictionaries, ontologies and text analytics to provide a rich data experience.

Customer benefits

“Researchers often find that critical information is trapped in text, unavailable for analysis and therefore ignored. Precious time is often spent trying to navigate the complexities of extracting value from unstructured sources in an effort to obtain a full view of their information,” said Michael Swartz, VP of Business Development and Strategy, Informatics, PerkinElmer.   “Our extensive scientific domain expertise, coupled with our knowledge of big data has enabled us to combine SciBite’s scientific dictionaries and ontologies with Attivio’s content analytics platform and TIBCO Spotfire’s visual analytics to create an advanced platform with complementary technologies. Our customers can significantly reduce time to insight and improve the quality of their decisions.”

“SciBite’s TERMite technology seamlessly integrates with Attivio allowing customers to aggregate, transform and visualize multiple forms of data with ease,” said Rob Greenwood, CEO of SciBite. “Designed by a team with decades of drug discovery experience, SciBite’s technology enables enterprise- level semantic transformation of data.  Our collaboration with PerkinElmer and Attivio leverages the strengths of our solutions to help scientists to make decisions based on all relevant information versus a partial picture.”

About SciBite

SciBite is headquartered in the UK and supports its global customer base with offices in both Cambridge UK & US and in Tokyo, Japan. SciBite’s semantic software suite includes a number of leading titles including TERMite, VOCabs, TExpress, and DOCstore.

To learn more about anything SciBite please contact us at [email protected] or visit our website at scibite.com.