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
- How can two enterprise organizations collaborate on open source pharma projects?
- What are the organizational changes required for adopting open source tooling?
- How can open source tools augment and improve propriety tooling?
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.