how Jumper 2.0 saved a life sciences company from the FDA.

A large life sciences company had spent several years and a few billion dollars developing a new drug. The future of this company depended on whether the new drug could get speedy approval from the Food and Drug Administration (FDA). The new drug application that had to be sent to the FDA would consist of tens of thousands of documents, images, and transactional data collected from research labs, clinics, commercial systems, and other sources.

In order to make the new drug development process more efficient, the life sciences company had deployed a leading integration solution to combine information systems used by the various process participants. The company faced a critical problem, however. The bulk of information produced in the new drug development process was unstructured. It included lab notes, molecular images, toxicology reports, patient records, dosing procedures, and other documents. How can they effectively link all the structured and unstructured information together?

Mapping the images and documents to rows in a relational database is not easy. Unstructured information is usually managed in one or more content management system such as Documentum or Interwoven. These systems, however, are not designed to integrate information from different repositories. They are used as a single consolidated place to store documents. Using a centralized content management system in a drug development process is not feasible since the process participants are often separated by administrative and company boundaries.

Linking the knowledge across each of these disparate data resources, mapping the correlations, attaching annotations and notes about the findings became increasingly challenging across multiple partners, vendors platforms, and storage solutions. Finding supporting documentation when it was needed across this morass was a needle in haystack.

What this life sciences company found was Jumper 2.0. A content and knowledge management solution that allowed them to link unstructured content to structured data. Jumper provided a universal search platform with knowledge capture features that provided the context necessary to locate the right documents when they needed them most, and to know how that document related to other documents or data stored in disparate repositories. This allowed adverse events and the cause of those events in sub-populations to be identified faster, to compare those results early in a clinical trial, to meet rigorous FDA requirements more easily and efficiently, leading ultimately to faster approval.

unleash the flow of knowledge

As profit and regulatory compliance pressures increase, life science companies are desperately seeking ways to decrease the cost of their clinical trials. Jumper speeds the knowledge transfer process so decisions can be made based upon real-time data and information from all systems to ensure the quality and integrity of the study. Jumper is a comprehensive system to aggregate, channel, and correlate for quick analysis the vast amount of diverse information being generated in the drug discovery and clinical development processes.

DOWNLOAD JUMPER NOW

Case Studies

• * Preclinical Research
• * Product Development
• * Complex Litigation
• * Education