The workshop provides a guided hands-on experience in the advanced use of Stan, rstan and Torsten for Bayesian PKPD modeling. Stan is a flexible open-source software tool for Bayesian data analysis using Hamiltonian Monte Carlo (HMC) simulation—a type of MCMC simulation. Torsten is a Stan extension containing a library of functions to simplify implementation of PKPD models. This workshop builds on the foundations presented in our previous introductory Stan workshops. Topics include model evaluation and comparison, models with systems of ODEs, optimizing Stan code, using MCMC results for population and trial simulations, and more. You will execute Bayesian data analysis examples using Stan. Via the examples, you will learn to implement population PKPD models including those involving censoring, numerical solution of ODEs, and user-defined probability distributions and likelihoods.
Download the zip file containing the course materials. Unzip the file. Navigate to the “script” directory. Open the R script file “pkgSetup.R” using your favorite R environment and run the script to install the R packages used in the course.