Practical R for the Pharmaceutical Industry
CSE-41396
Learn to Create Regulatory Compliance Deliverables for Pharmaceutical Industry: SDTMs, ADaMs, Tables, Lists and Graphs
Participants will gain comprehensive knowledge on common R packages (Tidyverse, DPLYR and Piping) and the R programming language. Attendees will learn how to access, create and process R data frames in data management, reporting and analysis. In addition, this course shows best practices in how to select, filter, derive, append and join data frames using SQL 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 Learning Highlights:
- 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
Course Outcomes:
- 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
Software: Base R, R Studio are required which are free to download
Hardware:
- 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
Course Typically Offered: Online in Summer and Winter quarters
Textbook required: None
Related certficiate program: R for Data Analytics
Contact: For more information about this course, please contact unex-techdata@ucsd.edu
Course Information
Course sessions
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
No textbook required.
Policies:
- No refunds after: 1/20/2025
Schedule:
Instructor:
Sunil Gupta, M.S.
Principal SAS CDISC Consultant, Gupta Programming
Sunil Gupta, MS, is an international speaker, best-selling author of five SAS books, and a global SAS Developer and CDISC SME and corporate trainer. Sunil is an advocate of CDISC automation and standardization with over twenty-five years of experience in the pharmaceutical industry. Most recently, Sunil is teaching Practical R for SAS Programmers, a CDISC online class at the University of California at San Diego, and classes on Data Science using SAS at UCLA and UCSD Extension. In 2019, Sunil published his fifth book, Clinical Data Quality Checks for CDISC Compliance Using SAS and in 2011, Sunil launched his unique SAS mentoring blog, SASSavvy.com, for smarter SAS searches and R-Guru.com for R Programming. Sunil has MS in Bioengineering from Clemson University and a BS in Applied Mathematics from the College of Charleston.
