The journey towards end-to-end (e2e) R-based regulatory submissions is one of the most significant transformations in our industry today. While the technical capabilities of R are clear, achieving success is a complex endeavor that requires more than just good code. This keynote draws inspiration from the classical strategic concept of "天时地利人和" (The Right Time, Place, and People) to frame the challenges and triumphs of this journey, using a successful e2e submission as a guiding case study.
Shifting from this framework to practice, we will analyze current R adoption trends across China's pharmaceutical landscape, from SDTM to TLG generation. Data reveals that while R is gaining strong traction in analysis and reporting, its use in foundational stages like SDTM creation remains a challenge. This observation leads to two key discussions: first, the pragmatic case for hybrid submissions, leveraging the strengths of both R and SAS, and second, the emerging role of Artificial Intelligence. We will touch upon how the industry is beginning to explore AI to solve complex challenges like SDTM mapping, discussing both the immense opportunities and the practical hurdles ahead.
Joe Zhu
Roche
From Harmony to Hybrid: Charting a Practical Course for R Adoption in Pharma
The journey towards end-to-end (e2e) R-based regulatory submissions is one of the most significant transformations in our industry today. While the technical capabilities of R are clear, achieving success is a complex endeavor that requires more than just good code. This keynote draws inspiration from the classical strategic concept of "天时地利人和" (The Right Time, Place, and People) to frame the challenges and triumphs of this journey, using a successful e2e submission as a guiding case study. Shifting from this framework to practice, we will analyze current R adoption trends across China's pharmaceutical landscape, from SDTM to TLG generation. Data reveals that while R is gaining strong traction in analysis and reporting, its use in foundational stages like SDTM creation remains a challenge. This observation leads to two key discussions first, the pragmatic case for hybrid submissions, leveraging the strengths of both R and SAS, and second, the emerging role of Artificial Intelligence. We will touch upon how the industry is beginning to explore AI to solve complex challenges like SDTM mapping, discussing both the immense opportunities and the practical hurdles ahead.