Lonza Split

Clinical Intake

Applying Technology to Cumbersome Data Sharing Processes in a Multi-Collaborative Environment

Current Practices

Today’s multi-collaborative nature of the life sciences industry is challenged with copious amounts of documents and data moving into and through the organization. Complex partner networks are creating data in massive quantities, coming from a variety of sources including trials’ sites, CROs, development partners, and M&A activity.

Often this externally created content is not readily available because of time-consuming, manual Clinical Intake processes for sharing and bringing data inhouse.  Lack of standards or the use of multiple standards by different partners make assessment and consolidation of data and documents slow and prone to error. Bringing this data into the organization and being able to use it in a meaningful way can be an arduous and expensive task. Duplication of content is common, data quality is questionable, and inconsistent data handling practices create limitations to the downstream use of data.  These ongoing challenges can result in an increased risk of noncompliance, impact inspection readiness and limit oversight. They also impact the team’s ability to trust the data and any decisions that are based on it.


Important Questions

  • How can this important data be operationalized across the organization?
  • Can organizations overcome the challenges of the variety, volume, and lack of standardization of their data to use it in a more meaningful way?
  • Can data-driven organizations harness the power of their, data, and content to inform business decisions?


An Innovative Answer

The NNIT team understands the business advantages locked away in this data. We are using novel technologies to automate the critical clinical intake process and deliver greater value from shared data. Our Clinical Intake Solution automates data and document intake using artificial intelligence and inhouse developed standards. The unique combination of expertise and automation helps teams understand their content, improve its quality, and effectively extract insights from it. The technology helps in scaling our domain knowledge, making it accessible throughout the intake process for greater efficiency.

By automating data quality assessments prior to intake, we can quickly identify inconsistencies. This creates a unique opportunity to enhance data based on best practices or reference data/document models. Using pre-built data governance libraries, we can create a large rule set to profile any data set. These rule sets act as accelerators and aid in aligning data to current standards including CDISC, TMF Reference Model, EVMPD, etc. They also help R&D teams identify incomplete or obsolete data more efficiently.

NNIT’s Clinical Intake Services combine cutting edge technology and domain expertise to accelerate the use of critical data across the organization. Whether you are supporting M&A activities, or simply trying to maintain compliance within your electronic trial master file, our Clinical Intake solution offers clarity. 

Contact us to learn how you can operationalize complex data more efficiently.