Modelling pulsatile profiles in NONMEM
A modellers challenge: getting data in front of you that don’t seem to fit any of the standard effect models and PKPD relationships. Especially in endocrinology, hormonal profiles are rarely …
Building your first PBPK model:the basics
In previous posts we referred exclusively to modelling using the top-down, population approach. However, in recent years, physiology-based, bottom-up approaches are getting more attention from both industry and regulators. Population …
Plotting PK/PD hysteresis with variability in R using ggplot
The identification of hysteresis in a PK/PD relationship provides information on a possible delay between the plasma concentration and the effect. The identification of hysteresis can further assist us in …
Modelling asymmetry in concentration-effect relationships
Introduction Why do we assume symmetry in our concentration-effect relationship? I recently came across an article published by Piet Hein van der Graaf and Rik Schoemaker from 1999 on the …
Validate your model with NPDE analysis
As part of the series of tutorials on model validation, I will get you started on doing your own Normalized Prediction Distribution Errors (NPDE) analysis. As the VPC and bootstrap, …
Get started to non-parametric bootstraps: execution and interpretation
Once you completed your model development, you now have a final model that fits your data the best and you’re now ready to validate your results. One way to internally …
Simulating your pharmacometric model with parameter uncertainty in R
How certain are we about the parameters that we estimate in our population model? Is that volume of distribution that NONMEM gave us really 10 liters with a clearance of …
From publication to simulation: extracting information from literature models – Amikacin case study
When you are starting to learn about the basics of modeling & simulation, or when you are planning to start a new study with an already existing compound, it could …
Creating a simple pharmacometric Shiny application with mrgsolve in R – Part 2
Shiny applications are a great way to show your complicated models in an interactive way. In recent years, many different examples have been published online showcasing a wide range of …
Creating a simple pharmacometric Shiny application with mrgsolve in R – Part 1
This two part series will show you how to create a simple pharmacometric Shiny application using the mrgsolve package in R. I think that Shiny applications are the most promising way …