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Case Study: The Reveal Overview


coverRapidly Retrieve Clinical Information across Multiple Data Sources: Introducing Reveal

The vast and disparate nature of clinical data challenges our ability to search and analyze. Using Reveal, you can now answer precise questions gleaning data from spanning disparate sources in seconds rather than hours. Questions like:

  • Where is GI Bleeding?
  • What hypertension events were seen across this compound?


Reveal’s search technology eliminates the need for multiple manual, time-intensive searches through various clinical data systems and uniquely reaches sources previously impossible to search. It bridges the gap between data and analytic tools so users avoid spending time hunting for the information and, instead, focus on the analysis to answer key scientific questions.

Shine A Light On Clinical Data

Pharmaceutical companies are awash in data, and it isn’t getting easier. Increased regulatory requirements, deepening medical sciences, and mergers and acquisitions are adding to ever growing mountains of data.

Search Far and Wide

Reveal is designed to perform a federated search across different repositories. You can build a single search index which includes multiple, heterogeneous data sources. Even if your data resides in different physical locations, Reveal can consolidate the information into one searchable body of knowledge.

Easy Search

To use Reveal, you simply type in clinical terms to find your data. There is no need for complicated query languages like SQL.

Narrow the Focus

Using metadata-powered search terms you can narrow your search to a study path.

In the full report, the following Case Studies are examined:

Case Study #1:

Post approval safety issues are being reported across a number of the company's drugs within Alzheimer's. The team needs to be able to search across studies to find data that might contain an increase in anxiety events and a potential interaction with Memantine, a common medication for Alzheimer's.

Case Study #2:

An entire submission has been outsourced to a CRO and that organization has delivered the data. All 14 studies in our submission should collect the ADAS-COG questionnaire. The CRO should have verified this result.

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