Sat, June 10, 2017
8:30 AM – 4:30 PM CEST
Budapest Congress Centre
Jagelló út 1-3
Workshop summary: We will provide 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 populatin 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.
Requirements for Attendees
Knowledge and experience in population PKPD modeling and the use of R and Stan. The workshop assumes a knowledge of Stan comparable to the content of our previous introductory workshops. For those who do not yet have the required knowledge of Stan we will offer a recorded online version of an introductory workshop prior to PAGE 2017.
Materials Provided by Metrum
Course slides, data and code for all examples, online access for one week to a cloud-based compute server on which the software used in the course is installed.
Course will be led by Metrum's Bill Gillespie, Ph.D., and Charles Margossian.
Satellite meeting at PAGE 2016 (Jun 10)
Free mrgsolve Workshop after ASCPT (Mar 12)