Organize, standardize and manage clinical research data and metadata quickly and efficiently. SAS Clinical Data Integration provides a foundation for defining analysis data sets and supporting strategic analyses, such as cross-study and advanced safety analysis, while automating repeatable clinical trial data integration tasks.
Increase operational efficiency while lowering costs.
SAS Clinical Data Integration automates repeatable tasks, which frees up resources for more strategic actions. The solution lets you manage and reuse information stored in a common repository, which reduced both development and maintenance time. That means you can write and validate less code, and potentially reuse code for future trials. As a result, you can scale clinical studies without adding expensive, hard-to-find headcount, as well as increase your capacity to handle additional trials – and more complex, global trials.
Drive top-line growth.
SAS Clinical Data Integration provides fast, efficient access to clinical, operational and safety data, regardless of location or source. This enables you to improve your time to market while containing clinical research costs. The software automates the migration of acquired data assets through data standards, while supporting and automating data aggregation and standardization for ongoing clinical trials. Faster data preparation also facilitates meeting the requirements of medical publications.
Ensure the proper use of standards.
SAS Clinical Data Integration standardizes data to CDISC SDTM, SEND, ADaM or custom data standards using prebuilt data models and processes. A visual interface lets you easily convert legacy data to standard data. And the flexibility of the solution ensures support for health care data standards of the future.
Deliver consistent, trusted and verifiable clinical information.
- Aggregate information from virtually any hardware platform or operating system.
- Address potential issues before they affect your study by automating data quality and data transformation routines.
- Build and document work with a user-friendly GUI interface.
- Reduce the need to write unique code for each study.
- Get new team members up to speed quickly on work done by others.
- Integrates clinical, operational and safety data from multiple sources.
- Prepares uniform, consistent data for analysis.
- Enhances data quality to ensure trustworthy analytical conclusions.
- Supports data standards and performs adherence checks.