This website was created to increase the documentation in the field of pharmacometrics. The website contains blog posts, pharmacometric tutorials, Shiny applications and a lot of example codes for R, mrgsolve and for NONMEM. All related to data analytics, population PK/PD, PBPK and pharmacometrics in general.

Latest posts

Learn about pharmacometrics and clinical pharmacology during your workout

I love to listen to podcasts while I am working out or going for a walk. However, I must admit that some of these podcasts are just a background conversation with nothing meaningful being said. While scrolling through LinkedIn I was therefore pleasantly surprised to see a post from Nathan Teuscher showing that he started the Clinical Pharmacology podcast! Nathan …

Introduction to pharmacometrics and its importance in drug development

Pharmacometrics is a rapidly growing field that combines pharmacology, mathematics, and statistics to optimize drug development and dosing. It is the science of quantifying drug effects in patients and developing mathematical models to understand and predict drug behavior in humans. Pharmacometricians use mathematical models to describe the relationship between drug exposure and response, and this can help in making informed … Read more

New shiny applications for PMX simulations!

A range of new shiny applications have been published on this website to visualise pharmacokinetic profiles over time and better understand the use of population models. All applications can be accessed from the Applications menu on this website. All code is updated on GitHub PK profile over time Simulate an oral pharmacokinetic profile based on the dose and model … Read more

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 semidefinite…, R matrix algorithmically singular…, etc.) or people ask and discuss whether or why the covariance step of the model was not successful. However, we barely pay any attention to … Read more

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 is visible, you should pay some attention on quantifying parallel absorption processes. Multiple absorption processes in one model may be used to describe complex absorption profiles of drugs. Indeed, a … Read more

Applying MAP Bayes estimation for therapeutic drug monitoring (TDM) in R with mrgsolve

The development of population PK (and PD) models enable the use of individual Bayesian dose optimization. One could use the included covariates to derive the dose of an individual but one could also determine what an individual’s clearance and/or volume of distribution is by measuring one or multiple plasma concentrations after the first dose. Especially when a narrow therapeutic window … Read more

Simulating the equi-dosing regimen region in R using mrgsolve – a bottom-up approach

Acknowledgments The idea for this post was based upon the research by Dr. Lloyd Bridge, presented at the British Pharmacological Society meeting December 2018. and published in October 2020 in JPKPD: Hof, F., Bridge, L.J. Exact solutions and equi-dosing regimen regions for multi-dose pharmacokinetics models with transit compartments. J Pharmacokinet Pharmacodyn (2020). Introduction When a PK(/PD) model is developed, it is … Read more

How (not) to report pharmacokinetic data

The correct reporting of pharmacokinetic data can provide a tremendous amount of information on the clinical pharmacological characteristics of a drug. Small studies with a limited number of plasma samples can already be informative for others, especially in special populations where information is already limited. However, regardless of the sample size of the study, from extensive phase 1 studies to … Read more

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 called the inter-individual variability or IIV. We also know that the there can be changes in these processes from one day to another, or between two dose administrations, which is … Read more