Certara announced that it is partnering with Thomson Reuters to provide its customers with access to Thomson Reuters Cortellis for Informatics life sciences content through its D360 platform. Certara’s D360 is an integrated solution for the query, analysis and visualization of drug discovery and development data.
D360 facilitates information sharing within and between a pharma company’s silos of discovery, pre-clinical and clinical data. This comprehensive data integration approach allows researchers to evaluate all pertinent information when they need to make critical decisions. D360 also empowers researchers to query and analyze their data without support from the IT team, enabling them to answer their questions as soon as they conceive them.
“This partnership will enable our mutual customers to integrate Thomson Reuters’ authoritative content with other proprietary and public data that they have integrated via the D360 platform,” said Joseph Donahue, senior vice president at Thomson Reuters. “We are pleased to be working with Certara to drive innovative solutions that support the research efforts and workflows of our customers.”
For example, D360 will enable researchers studying a particular drug receptor to retrieve published information within the solution on all the molecules attached to that receptor. By streamlining data gathering and analysis across internal and external sources, this enhanced form of D360 is expected to expedite decision making and accelerate the drug development process.
“Integration with Cortellis allows D360 to provide data views that present curated public data alongside a company’s internal proprietary data. Partnering with Thomson Reuters is another exciting step forward in ensuring that D360 remains the most usable and cost effective application for allowing scientists to easily get the data they need to make the best possible research decisions.” said Jonathan Feldmann, vice president, scientific informatics at Certara.
Cortellis for Informatics provides real-time, evidence-based information through application programming interfaces, which includes published experimental pharmacology, pharmacokinetic and pharmacodynamic results; clinical trial protocols and outcomes; competitive intelligence; patent information; and pharma company press releases and presentations. It also permits quantitative structure-activity relationship analyses of experimental results reported in published papers and patents. This data can be combined to develop an investigational drug pipeline database, and also to track competitor activity.