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Navigating the Shift: From SAS to R in Clinical Trials with Sunil Gupta

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Manage episode 451076358 series 3526489
Content provided by Sam Parnell & Ivanna Rosendal, Sam Parnell, and Ivanna Rosendal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sam Parnell & Ivanna Rosendal, Sam Parnell, and Ivanna Rosendal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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Why has SAS been the cornerstone of clinical trials for decades, and what is causing the shift to R now? Join us on "Transformation in Trials" as we explore this pivotal transition with Sunil Gupta, a seasoned programmer who has navigated both worlds. Sunil elaborates on SAS's long-standing dominance due to its robust programming capabilities and ease of use for FDA reviewers. However, the landscape is changing as R garners attention for its graphical prowess and collaborative potential. The conversation highlights the growing trend of new graduates versed in R and Python, which alleviates the shortage of SAS programmers and signifies a modernization wave in clinical trials, ultimately aiming to accelerate drug development.
Our discussion takes a deep dive into the collaborative spirit driving this transition, particularly through initiatives like Pharmaverse. This specialized extension of Tidyverse is designed to optimize clinical data workflows within the pharmaceutical industry. Sunil shares insights into how clinical programming is evolving, focusing on standardized data models and the unification of CDISC standards. The conversation underscores the importance of collaboration and resource sharing, allowing organizations to tackle complex challenges efficiently and improve patient outcomes while adapting to R's open-source environment and its growing acceptance in pharmaceutical submissions.
Transitioning from SAS to R is not just about adopting a new tool; it's about mastering new skills and embracing change. Sunil discusses the challenges he faced when learning R, from understanding its functional approach to navigating intricate syntax. He offers personal anecdotes that reflect his journey and the broader industry shift, emphasizing the importance of validation processes and resource optimization. As we conclude this episode, we express gratitude for the platform to discuss these transformative changes and invite listeners to engage with us on future topics, continuing to share success stories that inspire more organizations to embrace the power of R.

________
Reach out to Ivanna Rosendal
Join the conversation on our LinkedIn page

  continue reading

Chapters

1. Navigating the Shift: From SAS to R in Clinical Trials with Sunil Gupta (00:00:00)

2. Transition From SAS to R (00:00:18)

3. Collaboration and Pharmaverse in Clinical Programming (00:07:54)

4. Comparison of SAS and R Benefits (00:18:57)

5. Mastering R (00:26:13)

6. Podcast Networking and Promotion (00:34:13)

78 episodes

Artwork
iconShare
 
Manage episode 451076358 series 3526489
Content provided by Sam Parnell & Ivanna Rosendal, Sam Parnell, and Ivanna Rosendal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sam Parnell & Ivanna Rosendal, Sam Parnell, and Ivanna Rosendal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Send us a text

Why has SAS been the cornerstone of clinical trials for decades, and what is causing the shift to R now? Join us on "Transformation in Trials" as we explore this pivotal transition with Sunil Gupta, a seasoned programmer who has navigated both worlds. Sunil elaborates on SAS's long-standing dominance due to its robust programming capabilities and ease of use for FDA reviewers. However, the landscape is changing as R garners attention for its graphical prowess and collaborative potential. The conversation highlights the growing trend of new graduates versed in R and Python, which alleviates the shortage of SAS programmers and signifies a modernization wave in clinical trials, ultimately aiming to accelerate drug development.
Our discussion takes a deep dive into the collaborative spirit driving this transition, particularly through initiatives like Pharmaverse. This specialized extension of Tidyverse is designed to optimize clinical data workflows within the pharmaceutical industry. Sunil shares insights into how clinical programming is evolving, focusing on standardized data models and the unification of CDISC standards. The conversation underscores the importance of collaboration and resource sharing, allowing organizations to tackle complex challenges efficiently and improve patient outcomes while adapting to R's open-source environment and its growing acceptance in pharmaceutical submissions.
Transitioning from SAS to R is not just about adopting a new tool; it's about mastering new skills and embracing change. Sunil discusses the challenges he faced when learning R, from understanding its functional approach to navigating intricate syntax. He offers personal anecdotes that reflect his journey and the broader industry shift, emphasizing the importance of validation processes and resource optimization. As we conclude this episode, we express gratitude for the platform to discuss these transformative changes and invite listeners to engage with us on future topics, continuing to share success stories that inspire more organizations to embrace the power of R.

________
Reach out to Ivanna Rosendal
Join the conversation on our LinkedIn page

  continue reading

Chapters

1. Navigating the Shift: From SAS to R in Clinical Trials with Sunil Gupta (00:00:00)

2. Transition From SAS to R (00:00:18)

3. Collaboration and Pharmaverse in Clinical Programming (00:07:54)

4. Comparison of SAS and R Benefits (00:18:57)

5. Mastering R (00:26:13)

6. Podcast Networking and Promotion (00:34:13)

78 episodes

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