June 22nd at 10am ET
Interest in R and the open-source ecosystem is rapidly growing in the world of clinical programming. This conservative industry has begun to see the benefits that these tools can bring into the regulatory world. The potential of RStudio professional tools is astounding, with the power that R Markdown and Shiny can bring to statistical teams and their stakeholders – but the change is not as simple as swapping out one tool with a new one. Many programmers in the life sciences and pharma industries have spent their careers using a single programming language, and adopting a new language can be quite challenging. This webinar will explore some of the challenges of transitioning a clinical programming team to R and open-source tools alongside traditional SAS® programming models. The focus will be on questions such as adapting R to the typical workflows of a clinical programming team. Most importantly, this discussion will focus on the large challenge of upskilling programmers to a new and unfamiliar programming language and the associated process-based challenges.
What you will learn:
Director of Clinical Programing at GSK
Michael Rimler is a clinical programmer in GSK Biostatistics and passionate about influencing the evolving role of open source technologies and data science capabilities on clinical data analytics. He is involved with numerous internal initiatives aimed at moving the organization in this direction, including leading the effort to fully integrate R into the clinical reporting process. Michael is a co-lead of the Open Source Technologies in Clinical Research PHUSE working group project, has chaired a PHUSE US Single Day Event on Data Visualization, and will serve as a co-chair for the 2021 PHUSE US Connect.
Chief Innovation Officer at Atorus
Michael is the Chief Innovation Officer at Atorus Research. He has extensive CDISC experience, working with both Study Data Tabulation Model (SDTM) and Analysis Data Model (ADaM) standards, and serving as a subject matter expert for Define.xml. He holds a bachelor’s degree from Arcadia University, where he studied business administration, economics, and statistics. He is a 2020 UC Berkeley School of Information Master of Information and Data Science (MIDS) program graduate, where he worked on projects involving computer vision, natural language processing, cluster computing, and deep learning. His special interests include automation, machine learning, big data technology, and mentoring rising programmers.
Only 3,000 live attendees are allowed in the Webinar on a first come first serve basis. There will be approximately 45 minutes of presentation and about 15 minutes for Q&A.
We've started a Github repository with all webinar materials. Speakers for this webinar and all future webinars will add their materials to the repository.Go to the repo
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