Mitigating Risk, Improving Results: A Better Approach to Protocol Deviations
Webinars
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Clinical trial data continues to grow in complexity and variety, and the use of data continues to expand beyond submission-pathway statistical analyses. Maximizing the value of data while maintaining regulatory rigor and reducing cycle times is an increasing challenge for data managers, biostatisticians, statistical programmers, and data scientists. A statistical computing environment (SCE) is a necessary step to ensure that results are generated in a way that is transparent, auditable, and secure. However, as the needs evolve, so must our understanding of the technology used to support those needs.
Meet the increasing demands of modern clinical trials using elluminate and learn more on SCE within the elluminate Clinical Data Cloud and how it provides an analytic environment fully integrated with an end-to-end data platform, allowing teams to leverage data, metadata, standards, and code in a way that can evolve at pace with today’s trials. In this webinar, you will learn more about how the elluminate SCE takes advantage of a platform approach to increase automation, maximize data value, and accelerate trials.
What You Will Learn
Join this 30-minute webinar to learn how elluminate SCE:
- Increases development efficiency by providing access to all data and metadata across studies from a single location
- Streamlines workflows by tracking data dependencies and scheduling programs to execute automatically upon updates to data
- Increases rigor by enabling traceability and reproducibility of results through unified version tracking of code, data, metadata, and execution environment
Who Should Attend?
- Clinical Programmers
- Biostatistics
- 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.
