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R Papers (, R/Pharma Papers)

1. Exploring Use of R for Clinical Trials, Kalpesh Prajapati

2. Is R language reliable and efficient tool for programming SAS datasets or just art for art’s sake?, Piotr Podlewsk [DPLYR, SDTMs]

3. Clinical Trial Datasets (CDISC - SDTM/ADaM) Using R, Prasanna Murugesan [Compare SAS Code, Presentation]

4. A Gentle Introduction to R From A SAS Programmer's Perspective, Saranya Duraisamy [Beginner Level]

5. Python and R made easy for the SAS® Programmer, Janet Li [Compare Code]

6. R for SAS programmers: It’s different, but friendly, Friedrich Schuster

7. SAS® and R - stop choosing, start combining and get benefits!, Diana Bulaienko

8. SAS and R Playing Nice Together, David Edwards, Bella Feng, Brian Schultheiss

9. Can clinical trial data sets (CDSIC - SDTM/ADaM) be generated using R? Blog


10. R: Validation Hub - A RISK-BASED APPROACH FOR ASSESSING R PACKAGE ACCURACY WITHIN A VALIDATED INFRASTRUCTURE [FDA, IQ/OQ/PQ]


11. CRAN Task View: Clinical Trial Design, Monitoring, and Analysis (packages)

12. SAS® and R Working Together, Matthew Cohen [Date formats]

13. Best Practices for Reproducible Package Management in R

14. Techniques for writing robust R programs, Martin Gregory , Merck Serono [Presentation, Defensive Programming]

15. How do I select an R package for my clinical workflow?, Sean Lopp & Phil Bowsher [Validation, Documentation, Version Control, Common FAQs]

16. The Challenges of Validating R [Presentation]

17. Using R to Drive Agility in Clinical Reporting [GSK Presentation]

18. CDISC Dataset-XML – A new Dataset Structure for Clinical Trial Data Transport for Future Drug Submissions, Jörg Dillert [R4CDISC, R4DSXML]

19. End to End Interactive TLF using R Shiny, Rohit Banga


20. Is there any better option than SAS for TLFs? Yes, there R!, Niccolo Bassani [Presentation - ddply(), Proc REPORT]

21. A quick introduction to plyr, Sean Anderson [PLYR package splits data]

22. Using R Programming for Clinical Trial Data Analysis Blog

23. The SAS® Versus R Debate in Industry and Academia, Chelsea Loomis Lofland, Rebecca Ottesen [Compare SAS and R]

24. Using R in a Regulatory Environment: some FDA perspectives

25. Using R: Perspectives of a FDA Statistial Reviewer [Presentation]


26. R-Pharma Papers

27. R for Clinical Reporting, Yes - Let's Explore It!, Hao Meng, Yating Gu, Yeshashwini Chenna (SASxport, sas7bdat, dplyr, Survival Analysis)


28. Generating ADaM Compliant ADSL Dataset Using R, Vipin Kumpawat [SDTM]

29. Generating TFLs in R - Challenges and Successes compared to SAS, Amol Waykar, Kevin Kramer, Kalyani Komarasetti, Andrew Miskell

30. Using the R interface in SAS ® to Call R Functions and Transfer Data, Bruce Gilsen

31. Expand Your Skills from SAS® to R with No Complications, Andrii Korchak [DPLYR, %>%]

32. Simulation in SAS with Comparisons to R, Chelsea Loomis Lofland, Rebecca Ottesen

33. Normal is Boring, Let’s be Shiny: Managing Projects in Statistical Programming Using the RStudio® Shiny® App, Girish Kankipati, Hao Meng


34. Building Automations for Generating R and SAS Code Supporting Visualizations Across Multiple Therapeutic Areas, Anastasia Alexeeva, William Martersteck, and Mei Zhao

35. Effective Exposure-Response Data Visualization and Report by Combining the Power of R and SAS Programming, Shuozhi Zuo, Hong Yan

36. A Brief Introduction to Performing Statistical Analysis in SAS, R & Python, Erica Goodrich, Daniel Sturgeon

37. The Power of Data Visualization in R, Babych Oleksandr

38. Open-NCA – R Scripts for CDISC-based Pharmacokinetic Analysis, Peter Schaefer

39. Statistical Computing Environments in CDER, Paul Schuette

40. Use of R Script to Create Trial Summary (ts.xpt) Domains for Nonclinical SEND Studies, Bob Friedman, Xybion; Anthony Fata, William Varady, William Houser, Kevin Snyder

41. R Package Oriented Software Development Life Cycle in Regulated Clinical Trial Environments, Yalin Zhu, Rinki Jajoo, Clare Bai, Sarad Nepal, Daniel Woodie, Keaven Anderson, Yilong Zhang [Presentation, GxP, SDLC]


42. R for SDTM and ADaM Data [Poster]

43. R syntax for SAS programmers, Max Cherny [Beginner, Tidyverse, SDTMs]

44. Creating Graphs Simply with SAS® or R, John O’Leary, Jaclyn Scholl

45. Techniques for writing robust R programs, Martin Gregory , Merck Serono

46. Seamless R And SAS: For Shiny Visualizations, Pragathi Kotha Venkata [Presentation]

47. R for the Analysis of Clinical Data, Greg Jones [Presentation]

48. Numerical validation as a critical aspect in bringing R to the Clinical Research, Adrian Olszewski [R and SAS differences]

49. How much is it? Validation of Open-Source-Software Using the example of R, Peter Bewerunge [IQ/OQ/PQ]

50. Introducing LearnR package.

51. An Automation Proof of Concept of Periodic Reporting via R Shiny [PSUR/DSUR, Presentation]


52. Open-Source Development for Traditional Clinical Reporting, Mike Stackhouse, Nathan Kosiba

53. r2rtf – an R Package to Produce Rich Text Format (RTF) Tables and Figures, Siruo Wang, Simiao Ye, Keaven Anderson, Yilong Zhang

54. Validating R – Part of the Uphill Battle in the Pharmaceutical Industry, Peter Schaefer and Debra Fontana [Installation, Operational, Performance Qualifications]