Veeva CDB

Veeva CDB is designed to collect, clean, and transform clinical data from various sources, such as third-party EDCs, RTSM, eCOA, labs, and imaging systems. The data ingested from these sources is automatically harmonized and transformed into a single coherent package, ready for downstream processes.

In a central environment, data managers are empowered to generate and handle queries, while also communicating with data providers efficiently. The platform facilitates real-time collaboration among data management, medical, and analysis team members. It also features automatic change detection that highlights new or changed data for review and utilizes automated checks to identify discrepancies and manage queries accordingly.

To assist oversight teams, the system provides interactive dashboards for maintaining awareness of study health. These dashboards make it easier to monitor progress and make data-driven decisions.

Key Features and Benefits:

• Centralized Data Management: Data can be managed and queries can be addressed from one integrated system.
• Automation and Efficiency: Reduces the manual effort needed for data cleaning by 30-50%, thanks to automated change detection and task management.
• Comprehensive Oversight: Interactive dashboards allow oversight teams to stay informed about the study's progress.
• Enhanced Collaboration: Smooths the collaborative process for data reviewers across various functions, enabling faster and coordinated decision-making.

The platform promises significant impact, including a 30% reduction in cleaning efforts through automation, making it 50% easier to create listings, and automatically closing 78% of check queries. By harmonizing clinical data in a single platform, Veeva CDB facilitates faster database locks and allows for data exports anytime, streamlining the entire clinical data management process.

Prominent users of this platform, such as GSK and Syneos Health, highlight its ability to speed up data management tasks and enable access to real-time data without relying on batch processes, enhancing the overall efficiency and decision-making process in clinical trials.