After a brief introduction to mrgsolve (https://mrgsolve.github.io), we will discuss concepts and applications for using the package in R to simulate from pharmacokinetic (PK) and physiologically-based PK (PBPK) models, estimate parameters given a model and data, and visualize simulation results with a Shiny app. We will establish a basic framework for running optimization in R and work hands-on examples using different optimizers, including local and global search algorithms. Building on this framework, we will also illustrate related workflows including global and local sensitivity analysis. Finally, we will develop and deploy a Shiny app using Rstudio Connect, allowing interaction with the model and optimization results by non-modeling stakeholders.
Devin Pastoor | Kyle Baron
Metrum Research Group | Metrum Research Group
A PK & PBPK Modelling Workflow in R: Simulation, Optimization & Visualization
After a brief introduction to mrgsolve (https//mrgsolve.github.io), we will discuss concepts and applications for using the package in R to simulate from pharmacokinetic (PK) and physiologically-based PK (PBPK) models, estimate parameters given a model and data, and visualize simulation results with a Shiny app. We will establish a basic framework for running optimization in R and work hands-on examples using different optimizers, including local and global search algorithms. Building on this framework, we will also illustrate related workflows including global and local sensitivity analysis. Finally, we will develop and deploy a Shiny app using Rstudio Connect, allowing interaction with the model and optimization results by non-modeling stakeholders.