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Practical R for the Pharmaceutical Industry - Learn to Create Regulartory Compliance Deliberables for Pharmaceutical Industry: SDTMs, ADaMs, Tables, Lists and Graphs

This 20-hours online class teaches essential concepts about common R packages (Tidyverse, DPLYR and Piping) and the R programming language. Attendees learn how to access, create and process R data frames in data management, reporting and analysis. In addition, this class shows best practices in how to select, filter, derive, append and join data frames using SQL type code. Ideal for the pharma industry, examples of both SDTM and ADaM datasets will be created, which are important in the pharmaceutical industry. Finally, tables, lists and graphs will be created from SDTMs and ADaMs.

Course Highlights:
  • Learn setup process and import data types into R data frames
  • Master basic R programming concepts: Vectors, Data Frames, Data Management, Joins, Summarize and View
  • Understand and apply advanced R programming concepts: Piping command (%>%), DPLYR components and Tidyverse
  • Create regulartory compliance deliberables for pharmaceutical industry: SDTMs, ADaMs, Tables, Lists and Graphs 
Course Learning Outcomes:
  • Install R Packages and Load Libraries Exercises
  • Access CSV, Excel, and SAS Data sets Exercises
  • Create Variables as Vectors and Assign Values or read CSV, Excel, SAS file into Data Frames
  • Create Data Frames from Vectors
  • Data Management Operations and Functions
  • Summarize, Transpose, Format, Join, View and Display Data Frames
  • Tidyverse Package for Data Management
  • DPLYR for SQL
  • R Piping %>%
  • Create SDTMs and ADaMs
  • Summary Tables and Lists
  • Statistical Analysis
  • Create Graphs  
Software: Base R, R Studio are required which are free to download
An Intel-compatible platform running Windows 11, 10 /8.1/8 /7 /Vista /XP /2000 Windows Server 2022, 2019 /2016 /2012 /2008 /2003
At least 256 MB of RAM, a mouse, and enough disk space for recovered files, image files, etc.
A Mac computer with Apple Silicon, Intel, PowerPC G5 or PowerPC G4 processors.
At least 256 MB of RAM, a mouse, and

Course Typically Offered: Online in Summer and Winter
Textbook required: None
Prerequisite: None
Contact: : For more information about this course, please contact

Course Number: CSE-41396
Credit: 2.00 unit(s)
Related Certificate Programs: BiostatisticsData Mining for Advanced AnalyticsR for Data Analytics

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