Abbreviations and Terminology Used in Population Pharmacokinetics/Pharmacodynamic Models and in Pharmacometrics
This page provides an overview of the abbreviations and terminology commonly used in population PK/PD articles.
Publishing the covariance matrix of population models. Why not?
The information in the covariance matrix Everyone that has worked for longer than a day with NONMEM has a high probability of encountering error messages mentioning the covariance matrix (nonpositive …
Parallel fast-slow absorption – Modelling the Tortoise AND the Hare
Introduction Unsurprisingly, the absorption of drugs is a complex process. Should you try a first-order input? Zero-order? Both?! Especially when a bias in the model fit of your absorption phase …
Inter-individual and/or inter-occasion variability: what can we quantify in our models and what is the impact on simulations
Introduction We are not all the same. We know that there is variability originating from physiological differences in the pharmacokinetic and pharmacodynamic (PK/PD) processes between individuals in a population, also …
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 …
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 …
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 …
Getting your NONMEM dataset to work – DATA ERROR summary
Getting your dataset in the right format to work with NONMEM can be a terrible job. Getting all your observations, doses, dosing times, etc. from different Excel sheets collected in …
A step-by-step guide to prediction corrected visual predictive checks (VPC) of NONMEM models
Introduction Back in 2011, a very nice paper introducing the prediction corrected VPC was published by Bergstrand et al, titled: “Prediction-Corrected Visual Predictive Checks for Diagnosing Nonlinear Mixed-Effects Models” In …