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Tag: ggplot2

Personal blog / Tutorials

Exploring the Capabilities of ChatGPT: A Step-by-Step Guide to Creating a Pharmacokinetic Analysis Shiny App

With the introduction of ChatGPT I was interested to learn how ChatGPT in pharmacometrics might be applied and how this will impact my code writing tasks, especially for doing pharmacokinetic …

VPC Tutorial

A step-by-step guide to percentile visual predictive checks (VPC) of NONMEM models

This blog is an extension on the previously discussed scatter VPC. A percentile visual predictive check (VPC) can be used to compare the distribution of the observations with the simulated distributions …

VPC Tutorial

A step-by-step guide to confidence interval visual predictive checks (VPC) of NONMEM models

Last time, we focused on the percentile VPC, which was already quite an improvement to the scatter VPC but one may wonder when looking at a percentile VPC, how certain …

VPC Tutorial

A step-by-step guide to scatter visual predictive checks (VPC) of NONMEM models

There are many different ways to evaluate model performance, and sometimes it seems that there are even more ways to use a visual predictive check (VPC) for your population PK …

Tutorials

A step-by-step guide to goodness of fit figures of NONMEM models in R using ggplot2

Model evaluation is a critical step in model development. A very good paper on how to evaluate continuous data pharmacometric models was published by Nguyen et al. in 2017, this …

Recent posts:

  • Exploring the Capabilities of ChatGPT: A Step-by-Step Guide to Creating a Pharmacokinetic Analysis Shiny App
  • Using R Shiny applications in scientific research – Can you spot a drug effect on blinded pharmacodynamic data…?
  • New shiny applications for PMX simulations!
  • Abbreviations and Terminology Used in Population Pharmacokinetics/Pharmacodynamic Models and in Pharmacometrics
  • Publishing the covariance matrix of population models. Why not?
  • Parallel fast-slow absorption – Modelling the Tortoise AND the Hare
  • Applying MAP Bayes estimation for therapeutic drug monitoring (TDM) in R with mrgsolve
  • Simulating the equi-dosing regimen region in R using mrgsolve – a bottom-up approach
  • How (not) to report pharmacokinetic data
  • Inter-individual and/or inter-occasion variability: what can we quantify in our models and what is the impact on simulations
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