Workshop: R for Drug Development

RStudio and Novartis will be presenting a free workshop providing an overview of the Tidyverse, Shiny and R Markdown for the R user community at PAGE 2019. This is a great opportunity to learn and get inspired about new capabilities for creating compelling analyses with applications in drug development. No prior knowledge of R, RStudio or Shiny is needed. This short course will provide a hands-on introduction to flexible and powerful tools for statistical analysis, reproducible research and interactive visualizations. The hands-on course will include an overview of the Tidyverse for clinical data wrangling, how to build Shiny apps and R Markdown documents, as well as visualizations using HTML Widgets for R.  Immunogenicity assessments and other drug development examples, will be reviewed and generated for each topic.

For the workshop attendees, we will be providing a free RStudio training instance. A training server is created for users to use live during the session and nothing is required to install prior to the workshop.

Workshop Time: Monday, June 10th, 2019, 8:00 AM – 12:00 PM.

Workshop Location: The workshop will be near PAGE 2019 in Stockholm, Sweden. PAGE 2019 will be held at the Stockholm Waterfront Congress Centre (2 minutes walk from Stockholm Central train station, 20 minutes by train from Stockholm (Arlanda) airport).

Stockholm Waterfront Congress Centre
Nils Ericsons Plan 4, Stockholm

Materials Provided: Course slides, data, and code for all examples, online access to a cloud-based compute server on which the software used in the course is installed

Workshop Fee: This half day course is free however there are only 25 seats available – first come first served.

Registration: This is a pre-meeting workshop that requires registering for the PAGE 2019 meeting. Please register ASAP in view of the limited course capacity.

PAGE Workshop Registration

Below is information about the topics to be covered:

nlmixr is an R package for fitting general dynamic models, pharmacokinetic (PK) models and pharmacokinetic-pharmacodynamic (PKPD) models in particular, with either individual data or population data (nlmixr will be highlighted in various output types). The nlme and SAEM estimation routines can be accessed using a universal user interface (UUI), that provides universal model and parameter definition syntax and results in a fit object that can be used as input into the Xpose package.

The Tidyverse is a coherent system of packages for data manipulation, exploration and visualization that share a common design philosophy. The workshop will provide an introduction to clinical data wrangling with R that includes an overview of the packages dplyr, magrittr, tidyr, and ggplot2. Workshop examples will focus on applications in drug development to help maximize productivity for the main stages of the clinical workflow.

Shiny is an open-source R package that provides an elegant and powerful web framework for building web applications using R. Shiny combines the computational power of R with the interactivity of the modern web. Shiny helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge. An introduction to databases will be reviewed as well as R web APIs.

R Markdown is an authoring format that enables easy creation of dynamic documents, presentations, and reports from R. R Markdown documents help to support reproducible research and can be automatically regenerated whenever underlying R code or data changes. R Notebooks, as well as various types of R Markdown output, will be covered, including blogdown and bookdown.

The htmlwidgets package provides a framework for easily creating R bindings to JavaScript libraries. htmlwidgets work just like R plots except they produce interactive web visualizations. htmlwidgets and Crosstalk will be reviewed for implementing cross-widget interactions. Immunogenicity ADA and other visualizations will be generated in the workshop.

Course Instructors

Phil Bowsher
Phil BowsherDirector of Life Sciences & Healthcare
Phil is the Director of Healthcare and Life Sciences at RStudio and has over 10 years’ experience implementing analytical programs, specializing in interactive web application initiatives and reporting needs for life science companies. His work focuses on the use of R with applications in drug development and is a contributor to conferences promoting science through open data and software.
Matthew Fidler
Matthew FidlerAssociate Director Pharmacometrics at Novartis
Matt is a Pharmacometrician with over 12 years experience. He is the lead developer of the nlmixr and RxODE R packages, which implement nonlinear mixed effects modeling and ODE solving. He is also proficient in NONMEM, C++, C, R and various other open source software packages.