What challenges were seen in competitive R&D and clinical stages? What outcomes were measured in related trials? Does the drug I am creating have potential efficacy or safety challenges? What does the patient population look like?
These are the sort of critical business questions that many life science researchers need to answer. And now, there’s a solution that can help you.
We all know the importance of high quality content you can depend on when it comes to making key business decisions across the pharma life cycle. We also know that the best way to get from textual data to new insights is using natural language processing-based text analytics. And that’s where our partnership with Thomson Reuters comes in. We’ve worked together on a solution to bring Linguamatics market-leading text mining platform, I2E, together with Thomson Reuters Cortellis high-quality clinical and epidemiology content: Cortellis Informatics Clinical Text Analytics for I2E.
Cortellis Informatics Clinical Text Analytics for I2E applies the power of natural language processing-based text mining from Linguamatics I2E to Cortellis clinical and epidemiology content sets. Taking this approach allows users to rapidly extract relevant information using the advanced search capabilities of I2E. The solution also allows users to identify concepts using a rich set of combined vocabularies from Thomson Reuters and Linguamatics.
Through one single interface users can quickly and easily gain access to new insights to support R&D, clinical development and clinical operations. This is the first time a cloud-based text mining service has been applied to commercial grade clinical and epidemiology content. The wide-ranging content set consists of global clinical trial reports, literature, press releases, conferences and epidemiology data in a secure, ready-to-use on-demand format.
Key features of the solution include:
- High precision information extraction, using state of the art text analytics, combined with high quality, hand curated data
- Search using a combination of Cortellis ontologies, plus domain specific and proprietary ontologies.
- Find numeric information e.g. experimental assay results, patient numbers, trial outcome timepoints, financial values, dates.
- Generate data tables to support you in your preclinical studies, trial design, and in understanding the impact of clinical trials.
- Generate new hypotheses through identification of entity relationships in unstructured text e.g. assay and indication.