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Free R resources for pharma programmers
Start learning R without spending anything. This hub collects the podcasts, conference papers, workflow diagrams, and book reviews Sunil Gupta has produced for SAS programmers moving to R in clinical trials.
Everything here is free to read and watch. Take what you need, and come back when you want the structured path.
Jump to: Watch and listen | Conference papers | R workflow diagrams | R book reviews | Where Sunil is speaking next
Podcast and webinar appearances where Sunil explains the SAS to R shift, what R does well in clinical trials, and how open source fits into regulated work.
1. R Guru SAS to R Tips by Sunil Gupta
2. Navigating the Shift: From SAS to R in Clinical Trials
3. Let's Talk About R (The Biometrics Leadership Lab), the Role of R in Clinical Research
4. Open Source Technology in Clinical Trials
Conference papers presented at WUSS, PHUSE, and PharmaSUG, including the WUSS 2025 Best Paper Award winner. Free to download.
Learning R from SAS
R Made Easier for SAS Programmers [WUSS Best Paper Award, 2025]
Reach for R Low Hanging Fruit for Faster Results [WUSS Best Paper Award, 2025]
R and Pharmaverse Trends [PHUSE, 2024]
R Package Validation and CDISC compliance
Programming in R Now? Why Exactly Is R Package Validation Required? [Clinical Data Standards Hub Blog]
R Shiny Applications
Visual maps of the R processes pharma programmers use daily, from data frame development through the full clinical trial workflow.
Make the migration from SAS to R smoother with side-by-side code comparisons.
Maximize pharmaverse for SDTMs, Admirals and TLGs without re-inventing the wheel.
Sunil has been invited to review four R books. Each review covers who the book suits, how it reads, and whether it earns a place on your shelf.
Data Wrangling with R book review by Sunil Gupta
I have the honor to review Data Wrangling with R by Gustavo Santos! Being new to R, I was afraid this book was going to be too technical and only on statistical modeling. On the contrary, I was happy to find this R book easy to read, understand and apply whether you are new or an intermediate R programmer. The logical flow between chapters and sections with useful summaries and tips showcase Gustavo's in-depth knowledge and expertise in R. I really like how Gustavo compares similar R methods which help to reinforce R syntax understanding. Gustavo's approach will be liked by Data Scientists since all traditional methods of data cleaning, structure and operations before statistical modeling are followed. The graph gallery makes it easy to look up the correct R graph code without writing R code from scratch. I highly recommend Data Wrangling with R book to establish a strong foundation of R learning!
R Bioinformatics Book review by Sunil Gupta
While this book is ideal for biomedical applications, the author transforms this complex topic to a language that is easier to read! The step-by-step instructions follow a cookbook similar to recipes. It is obvious the author has in-depth knowledge and real-world hands-on experience with R. The book has sections for each bioinformatics subtopic to explain tasks, how and what R codes to execute, line by line, and references for more information. This blueprint is ideal to help guide readers of all levels.
This book has good structure and programming style as well as logical content. A complete end-to-end work flow process is reviewed with the appropriate R packages as solutions to complete tasks. This saves reader’s time so they do not have to search and review R packages. In addition, when ready, readers can produce publication quality tables or graphs to share or to post online as Shiny apps. Readers in this field can jump start their understanding and progress toward getting projects started as well as keeping to tight deadlines!
Introduction to R for Social Scientists book review by Sunil Gupta
The authors do a good job of explaining why and how programmers should use R! This book is ideal for social scientists but also good for all industries since it does not assume prior knowledge of R and also addresses R learning pain points. The book examples are based on real-world applications and the R syntax is explained in easy to understand language. The book is unique because it divides exercises into three levels: Easy, Intermediate and Advanced for all levels of R programmers. The step-by-step guide helps new R programmers stay on the workflow as well as apply best practices. The R examples show various options for each function which helps R programmers understand the function better. Finally, the essential programming chapter is great since all R programmers need to learn and master these R concepts.
Extending R Book review by Sunil Gupta
True to the book’s name, Extending R is full of R history, scope, structure and applications. R enthusiasts will be happy to access the comprehensive wealth of information, explanations and examples all in one place. This unique book extends R with a separate section and chapters for each interface language. So, if you are a Python or Java programmer, for example, you can apply the programming tips to save you time when building applications.
In the advanced technical world of R, this book helps guide programmers to object-oriented programming principles, classes, methods, fields, functions and packages. Also included are data conversion sections to help with data and system migrations. Extending R is a reference dictionary with a glossary of terms as well as research and mathematical analysis.
Upcoming conferences, webinars, and UCSD classes.
Jul 7 - Aug 22, 2026, Practical R for the Pharmaceutical Industry, UCSD on-line class
Mar 14 - 18, 2027, PHUSE US Connect, Dallas TX
Jun 6-9, 2027, PharmaSUG, Anaheim, CA
Want the structured path?
These free resources answer specific questions. The mentoring program answers them in order, with exercises and 1:1 support, so you are productive in R within weeks.
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