Change management

Chairs: Cassie Murcray and Dror Berel

Summary: Transitioning from SAS to R in the Pharmaceutical Industry

Over the past two years, there has been a significant shift in the pharmaceutical industry from SAS to R, driven by the rising costs of SAS licenses and the influx of new talent trained in R and other open-source tools. Despite these trends, the industry’s conservative nature, particularly in a highly regulated environment, often results in a reluctance to change well-established practices.

As of 2024, this transition is well underway, with several companies already setting timelines for a complete migration to R. This includes replicating legacy SAS code in R for ongoing and long-term studies, as well as opting not to renew SAS licenses. While some SAS programmers find the transition to R more intuitive, others may face significant challenges.

Supporting SAS Programmers in Transitioning to R

To facilitate the learning process for SAS programmers, various strategies can be employed:

Traditional Training and Mentorship

Programs such as Posit Academy and mentoring from experienced R programmers are essential. Large organizations often establish Centers of Excellence, where a designated “R floating buddy” mentors SAS programmers throughout the various stages of learning R. This mentorship should be conducted with patience and empathy, recognizing the challenges of adapting to a new programming language with different principles and syntax.

Strategic Learning Approaches

Address Key Pain Points: Focus on demonstrating how specific challenges are effectively resolved with R, highlighting the value of the R-based solution, and celebrating small wins to foster continued learning.
Simplify the Learning Ecosystem: Introduce a simple set of R packages, such as the tidyverse, before gradually introducing more advanced concepts. Avoid overwhelming learners with multiple equivalent approaches.
Gradual Progression: Start with basic concepts and gradually introduce more advanced topics like version control, beginning with individual contributions and progressing to collaborative work.

Managing the Transition

The successful shift from SAS to R requires active management by senior leadership, including clear directives, timelines, and ongoing support. It is crucial to allocate time for learning while maintaining productivity on ongoing projects.

Action Items

To support this transition, the following resources should be developed:

Cheat Sheets: Create reference guides with common code examples translated from SAS to R.
Cross-Tool Comparison: Develop a Comparative Analysis of Methods and Implementations in SAS, R, and Python (CAMIS) to help programmers understand the default parameters and methods used in each tool.

This transition will not happen organically; it requires deliberate management and a structured approach to ensure successful adoption of R across the industry.