Case Study

Partnering with CCC to Support Contextualized Scientific Discovery

A global biopharmaceutical company headquartered in the U.K. saw an opportunity to further the organization’s mission of delivering value to current and future patients by transforming how they make digital assets available to the broader R&D organization.

CCC’s platform capabilities in contextualized discovery, enhanced by machine learning, enable individuals to find the right content at the right time. Building on this foundation, the company and CCC collaborated to define workflow features based on user need and requests. Additionally, the custom branding throughout the tool conveyed to researchers that they were using a solution unique to their organization.

Today, these are some of the key features they utilize:

  • Unified search experience: Using a scalable integration framework of data source connectors, researchers now have : single access point that brings together more than 10 data types, comprising more than 120 million records.
  • Personalized experience: Through both explicit and implicit personalization, the solution displays the data and content most meaningful to each user. User topic and data source preferences, search activity, sharing, purchasing history, and more are taken into consideration.
  • Dynamic data visualizations: Now, researchers can explore connections between scientific concepts more easily with dynamic visualizations of semantically enriched data

I'm a believer that 90% of what I need is published. I just need to find it. I want to create the story and then have all the references to prove it.”

—Early Phase Researcher, Biopharmaceutical Company

The Unified Data Sources Comprise:

  • 3 Million+ Grants
  • 350K+ Clinical Trials
  • 34 Million+ Patents
  • 100 Million+ Journal Articles and Book Chapters
  • 100K+ Drug Records
  • 9k+ Company Records
  • 7 Million+ Meeting Abstracts
  • 100K+ News Briefs
  • 1000 Market Research Reports

What is FAIR Data?

Findable, Accessible, Interoperable, Reusable.
These are the guiding principles that together add up to a “FAIR” way to manage scientific data.
This concept is not only important for the pharma industry, but for digital healthcare as a whole. FAIR began in the academic community and has since been embraced by scientific funding agencies such as the European Commission’s ERC (European Research Council), as well as the National Institutes of Health in the U.S.

Interested in more information on this project?

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