The Future of R in Clinical Programming | Episode 14

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Episode Summary

In this episode, we sit down with David, an expert in R programming for clinical trials, to discuss the evolving landscape of statistical programming. From his unconventional journey from journalism and philosophy into programming to his deep insights on the maintainability and stability of R in the pharmaceutical industry, David shares his perspective on the challenges and opportunities of open-source programming. He explores the key differences between R and SAS, the critical importance of backward compatibility, and how organizations can future-proof their R-based systems. David also introduces his work on PackageDiff, a tool aimed at addressing package stability, and shares his thoughts on AI's role in the space. This is a must-listen for anyone working with R in regulated environments.

Key Topics Discussed:

• David’s transition from journalism to programming
• The shift from SAS to open-source in the industry
• Why maintainability and stability are crucial for R adoption
• The challenges of backward compatibility and how to address them
• Community-led solutions vs. individual company validations
• Tools like Docker and Renv for managing R environments
• The role of AI in programming efficiency
• Predictions on whether R will overtake SAS in clinical trials
• A call for cultural change in how the pharmaceutical industry approaches R

About The Verisian Community Podcast

The Verisian Community Podcast brings together experts in clinical trials to exchange innovative ideas and best practices central to clinical reporting, submission and review. Aligned with Verisian's mission to accelerate the evaluation and market launch of new medical treatments, each episode features expert insights, with guests ranging from statistical programmers to medical writers, to discuss the challenges and opportunities of the latest software and technology.

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