Mitigating Risk, Improving Results: A Better Approach to Protocol Deviations
Webinars
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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
Who Should Attend?
- Data Managers
- Clinical Programmers
- Data Standards Specialists
- External Data leaders
Presenter
Vice President, Product Management, eClinical Solutions
Nathan Johnson is Vice President of Product Management at eClinical Solutions. With 20 years of experience in clinical research, Nathan is an accomplished innovator and programmer with deep expertise in statistical analysis, SAS programming, standards development, and data management. He is passionate about revolutionizing clinical trials through digital transformation, intelligent technologies, and enhanced automation. Nathan holds a Master’s degree in Biostatistics from Case Western Reserve University.
