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Parexel launches real-world data service offering

Wednesday, September 6, 2017

Parexel International, a global biopharmaceutical services provider, has launched a new end-to-end service offering to provide real-world data insights that help life science companies more effectively demonstrate product value.

“In an increasingly competitive market, leveraging data to demonstrate value is critical. However, unstructured data can make it difficult to overcome gaps in real-world evidence,” said Joshua Schultz, Senior Vice President and Worldwide Head of Parexel Access. “Our new service will allow clients to more seamlessly collect and communicate the specific data that payers, physicians, and patients require to establish that a new product offers greater benefits than the existing standard of care.”

Parexel’s new offering delivers fit-for-purpose real-world data strategies designed to accelerate market access and mitigate commercial risk. By addressing key factors necessary to demonstrate a product’s value during late-stage development, as well as before and after launch, the offering enables clients to provide high quality evidence that highlights a drug’s unique value.

To deliver this service, Parexel has developed a new dedicated real-world data service team with expertise in epidemiology, health economics and outcomes research, market access, analytics, medical sciences, and safety. The group is an expansion of the Parexel Access unit, which provides a complete and simplified solution encompassing evidence-based services throughout the product lifecycle.

The new offering is the latest addition to Parexel’s Connected Journey of more than 40 data-driven services. The service’s advanced data-aggregation capabilities help assure that clients have access to critical intelligence to inform and support value demonstration. Through these capabilities, primary and secondary data are combined from multiple sources, such as healthcare providers, patient reported outcomes, and electronic data capture, and are leveraged for optimal execution of late-stage programs.

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