Clinical data is growing in volume and variability. It’s no secret that tracking and maintaining data standards, global forms and programming libraries is a complex undertaking. Trial sponsors without robust data management solutions risk inaccurate reporting and time-consuming analysis which could potentially affect patient outcomes and/or filing timelines. In addition, clinical trial managers are now being asked to deliver near real-time data visualization and data surveillance, nearly impossible without comprehensive end-to-end application of data standards, from protocol through to submission.
Especially challenging for predefined solutions, each organization has a unique set of legacy data, current systems, tool sets and technologies. A customized approach can address all these factors and improve metadata management to improve study builds and ease standards compliance. Customization best leverages each organization’s existing infrastructure investment and statistical programming use case requirements to accelerate data reporting while improving data standards governance.
Implementation of a Statistical Computing Environment (SCE) yields the following benefits:
- Connection to any source data set
- Automated manual processes in clinical trials biostatistics and programming
- Ability to conduct regulatory and exploratory analytics in a single location
- Improved connections to data visualization tools to support surveillance
- Reusability, process automation and end-to-end data traceability