Utilizing elluminate Mapper for Compliant Submission-Ready SDTM Data
Presenter: Nathan JohnsonRecorded Live: Thursday, August 26, 2021
30-Minute Academy Webinar
elluminate Mapper for SDTM Data
As sources of clinical trial data continue to grow in complexity and variety, CROs and sponsors are experiencing the benefits but also realizing the challenges of data standardization at scale.
Additionally, with the increased pace at which meaningful insights are required of data in clinical research, the timeliness and quality of tabulated datasets, such as CDISC SDTM, have never been more critical.
elluminate® Mapper allows for rapid transformation of data from numerous sources and formats to industry or custom standards. The graphical tools and reusability within Mapper remove the need for custom and ad-hoc programming – all within a fully compliant and auditable environment. Clinical programming teams and data analysts use Mapper’s graphical user interface to generate full compliant SDTM datasets including:
- Reduce costs and increase control by enabling data analysts to map to clinical data standards including SDTM, instead of relying on SAS programmers or third parties
- Provide instant feedback about standards compliance with SDTM validation – even before mapping is executed
- Save time with dynamic mapping templates that map different types of data automatically upon receipt
- Simplify the process of mapping to standards with new specification authoring capabilities
“The official SDTM datasets used to support the primary analysis were programmed within the elluminate platform. We achieved excellent Pinnacle 21 scores as well, demonstrating elluminate’s ability to produce compliant, submission-worthy SDTM.”
– Bob O’connor, Associate Director, Clinical Data Systems, CDISC Technicon, 2021
Who Should Attend?
- Data Managers
- Clinical Programmers
- Data Standards Specialists
- External Data leaders
Nathan Johnson is Vice President, Digital Innovation at eClinical Solutions. Nathan has 20 years experience in clinical research as an innovator and programmer with expertise in statistical analysis and reporting, SAS programming, standards development, and data management. He is passionate about reshaping clinical trials through digital transformation, intelligent technology, and increased automation. Nathan has a Masters in biostatistics from Case Western Reserve University.