Atorus Academy Seminar
For the first time, the team at Atorus Research is excited to offer our Instructor-Led trainings to the general public.
Introducing the Atorus Academy Seminar Series
The Seminar Series provides the same practical, instructor-led training previously delivered through company-exclusive programs – now available through individual seat enrollment!
Whether you're a clinical SAS® programmer beginning your transition to R, or an R programmer seeking deeper mastery over clinical workflows, our Seminar Series will help you build the skills to use R confidently throughout the clinical data pipeline.
Enrollment is limited to 25 learners so act fast to secure your seat today!
You can sign up individually or as a group by reaching out to academy@atorusresearch.com
Clinical R Training Designed for Real-World Application
The open-source ecosystem offers an enormous and constantly expanding range of packages, tools, and possible workflows. Knowing which tools are appropriate for clinical programming, and how to use them effectively, can be difficult to navigate alone. Atorus Academy helps learners cut through that complexity. Join the thousands of clinical programmers and scientists from across the pharmaceutical industry who have trusted Atorus with their upskill to R.
Our instructors combine clinical programming experience, open-source expertise, and a practical understanding of the regulated pharmaceutical environment. Throughout our Seminar Series, learners will work with R packages and workflows selected specifically for clinical use cases.
The emphasis is not just learning R syntax. You'll also learn how to apply R to work clinical programmers are expected to perform. We've sat in your seats and know what the job entails – let us help sift through the noise of the ever-growing open-source world and show you how to leverage appropriate R packages for use cases within the clinical industry.
What You Will Learn
Through completion of the Seminar Series, learners will gain practical experience with:
- Fundamentals of the R programming language
- Base R, tidyverse, and pharmaverse packages
- Importing, mainpulating, and preparing clinical data within RStudio
- How to use base R and they tidyverse to program basic SDTM and ADaM datasets
- Using sdtm.oak for SDTM dataset programming
- Using admiral for ADaM dataset programming
- Creating, styling, and outputting clinical summary tables with Tplyr and clinify
- Creating clinical figures with ggplot2
- Applying these skills through guided exercises
What is Included?
- 16 live, instructor-led sessions
- 34 hours of training
- Guided programming practice during each course
- Opportunities to ask questions directly to experienced instructors
- Practical instruction focused on clinical programming use cases
- A final assignment workshop with instructor support
- Training across the major stages of clinical dataset and display production
Sessions are delivered live and synchronously through Microsoft Teams.
Schedule
The Seminar Series will meet on Wednesday at 11:00 a.m. Eastern Time, beginning January 20 and concluding May 26
Course Schedule
| Course | Session | Date |
|---|---|---|
| Introduction to R | Transitioning from SAS® to R — Part 1 | January 20 2027 |
| Transitioning from SAS® to R — Part 2 | January 27 2027 | |
| Transitioning from SAS® to R — Part 3 | February 3 2027 | |
| Transitioning from SAS® to R — Part 4 | February 10 2027 | |
| Using the tidyverse for Clinical Programming | February 24 2027 | |
| Creating Datasets in R | General Dataset Concepts | March 3 2027 |
| Basic SDTM Programming Techniques | March 10 2027 | |
| Programming SDTMs with sdtm.oak | March 24 2027 | |
| Basic ADaM Programming Techniques | April 7 2027 | |
| Programming ADaMs with admiral | April 14 2027 | |
| Creating Tables in R | Building Clinical Summaries with Tplyr — Part 1 | April 21 2027 |
| Building Clinical Summaries with Tplyr — Part 2 | April 28 2027 | |
| Building Clinical Summaries with Tplyr — Part 3 | May 5 2027 | |
| Producing a Styled Table | May 12 2027 | |
| Creating Figures in R | Building Clinical Figures with ggplot2 | May 19 2027 |
| Post-Course Assigment | Review and Q&A for Dataset, Table, and Figure Assignment | May 26 2027 |
For a complete breakdown of topics and skills covered in each Course, please see the Seminar Series Curriculum.
Seminar Series Curriculum
Introduction to R
5 sessions | 11 hours total
Begin your transition from SAS® to R with a practical introduction designed specifically for clinical programmers!
Using side-by-side examples, learners will connect familiar SAS® concepts with R syntax and workflows. The course covers core programming concepts, data and object types, common data transformations, importing and exporting files, and essential tidyverse packages.
Topics include:
- R terminology and programming fundamentals
- Introduction to base R, tidyverse, and pharmaverse
- Data types, objects
- Reading SAS® datasets and transport files
- R approaches to common SAS® data step options and procedures
- PROC PRINT, PROC MEANS, PROC SORT, and more!
- Data transformations and if/else logic
- Working with tidyverse packages: dplyr, tidyr, readr, stringr, forcats, and more!
Creating Datasets in R
5 sessions | 10 hours total
Learn how to create clinical datasets using base R, tidyverse workflows, and key pharmaverse tools.
Learners will apply practical techniques for deriving and assembling SDTM and ADaM datasets, with an emphasis on consistent, reproducible programming workflows.
Topics include:
- Working with dates, times, and date-times
- Managing missing data
- Derivations using conditions and calculations
- Fundamental SDTM and ADaM programming techniques
- Programming SDTM datasets with sdtm.oak
- Programming ADaM datasets with admiral
Creating Tables in R
4 sessions | 8 hours total
Develop reproducible workflows for creating clinical tables in R.
Learners will use Tplyr to build clinical summaries and clinify to organize, style, and output beautifully formatted tables
Topics include:
- Building and configuring Tplyr tables
- Count and shift layers
- Descriptive statistics summary tables
- Formatting and outputting submission-ready table
Creating Figures in R
1 sessions | 3 hours total
Learners will develop a structured, reproducible approach to creating commonly used clinical figures.
Topics include:
- Building and modifying ggplot2 visualizations
- Creating scatter plots and line plots
- Controlling plot appearance
- Creating summary information
- Combining plots and supporting summaries
Post-Course Assignment Workshop
1 session | 2 hours
You've invested time and energy into training – now let's see what we can do! Bring your new skills together to complete a dataset, table, and figure assignment, essentially a mock delivery showcasing your new abilities with R.
During this instructor-supported workshop, learners will have dedicated time to work through the assignment, ask questions, troubleshoot challenges, and review solution strategies.
Seminar Terms and Conditions
To see the Terms and Conditions click here
Enrollment and Pricing
The full Seminar Series costs $3,400 per learner.
Learners may enroll individually or as part of a small team. Because the Seminar Series uses a shared-seat model, employees from multiple organizations may attend the same training series.
Enrollment is limited to 25 learners to maintain an interactive learning environment.
To enroll or ask questions about group registration, contact: