Dear Members,

The GMP is thrilled to invite you to our upcoming online R for pharmacometricians workshop in 2024!

R is a versatile language and environment used for statistical computing and graphics. It offers a wide range of statistical techniques such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more. Additionally, R’s graphics capabilities allow the production of well-designed, publication-quality plots, complete with mathematical symbols and formulas.

An important advantage of R is its versatility. It provides an open-source route for participating in statistical methodology research, with the S language being a popular choice in this field.

R can be freely accessed as Free Software under the GNU General Public License. It can be compiled and run on various UNIX platforms, Windows, and MacOS.

The objective of this workshop is to provide beginners with a solid bases in R and to equip participants with the skills to analyze data, create models and simulations, as well as generate graphs.

Before attending the webinar series, please be sure to install R and RStudio on your computer (seek help from your IT department if needed). installation guide is available HERE.

The registration to this workshop is opened to Academic and Industrial members only and will give access to the 4 sessions.

The workshop will be split into four sessions, which are as follows:

Session 1 Beginner level (May, 13th, 2:00 p.m): Introduction to R and R studio by Rachid EL GALTA (Sandoz) – 2 hours including breaks

The goal of this session is to be able to read a dataset, do basic analysis and basic plots

Intro Material 

• R
• Rstudio 
• Scripts 
• Installing Packages in R 

Reading/Writing Data (import/Export Data) 

• Csv and txt 
• Excel 
• SAS 

Data visualization 

• Plots, histograms, barplots, boxplots, etc. 

Objects  

• Data Types 
• Data Structures: 
• Vectors, matrices, arrays 
• Lists 
• Data frames 
• Operators: 
• Arithmetic, Logical, Relational and Assignment  

Basic Commands 

• General functions 
• Data handling functions 
• Statistical functions 
• Handling Characters 
• Probability distributions 
• Conditional statement (if-else) 
• Loops 

Session 2: intermediate level (June, 21st 2024, 2 p.m.) by Thibaud Derippe (AstraZeneca) – 3 hours including breaks

The goals of this session is to handle all types of data and perform basic/intermediate PK analysis

• Introduction and session using Rmarkdown 
• New type of data: factor and data (showing forcats and lubridate pck)  
• PK specific workshop: generate PK dataset (eg in nonmem format in a stepwise approach) using joins (for cov), bind_rows etc 
• Concept of pipe (%>%) solving a readability and workability issues 
• Reviews of the main function of the tidyverse (mutate, filter, slice, select, arrange, if_else…) 
• Group_by %>% summary   
• Regression
• First ggplot 
• Gather function to combined with ggplot’s aes() 
• One PK example/work using all concept above: load a PK dataset, plotting the profile, compute stats, use a NCA package, and plot NCA results vs dose level?  
• Final PK workshop: introduction to RxODE simulations, and create some sort of function around it? 

Session 3: Advanced level (September, 4th 2024, 2 p.m.) by Thibaud Derippe (AstraZeneca) – 3 hours including breaks

The goal of this session is to use function and list to its full potential  

Toward fully functional programming  

• Advanced structure explanation  
• Full power of list with mapping functions 
• Fully functional programming 

Other demonstration

• regular expression 
• First Shiny app

Session 4: Forest plots in practical use (Oct, 10th 2024, 2:30 pm): Interpretation and implementation using the R-package ‘PMX Forest’ by Niclas Jonsson and Fanny Gallais (Pharmetheus) – 2.5 hours (including breaks)

Forest plots, as recommended by the FDA in their latest Population PK guidance, is becoming a standard component of submission packages, and can be used to efficiently summarize the impact of covariates on parameters from population models, as well as to illustrate the outcome in important patient subgroups. The webinar will cover both theory and practice regarding the creation of Forest plots in R, based on output from different types of models and covariate modeling techniques.