Population and ODE-based models using Stan and Torsten

Presented 20-21 August 2019 at StanCon in Cambridge, UK by instructors Charles Margossian and Yi Zhang, Ph.D.

This class covered techniques to build, fit, and criticize Bayesian models in pharmacometrics. When handling such models, we must address the following challenges: (i) the data generating process involves solutions to ODE systems; (ii) these ODEs are embedded in a complicated event schedule; (iii) the data comes from various sources, for instance, various patients and studies, and the resulting models are hierarchical.

The course reviewed elementary techniques to solve ODEs in Stan, the efficient parametrization of hierarchical models, and within-chain parallelization. We also introduced Torsten, an extension of Stan for pharmacometrics, which allows us to seamlessly combine the above methods.

Slides from the workshop can be found here.