Students of Bio-Pharmaceutical Sciences, and external students enrolled in a biomedical master program, with adequate knowledge of pharmacology and pharmacokinetics, and statistics.
This lecture series aims to provide a conceptual and broad overview of the principles of pharmacokinetic-pharmacodynamic (PK-PD) and pharmacometrics modeling, illustrated by examples if multiple therapeutic areas. We also discuss the mathematical basis of these models such as ordinary differential equations and nonlinear mixed effect modeling. Topics to be discussed include pharmacokinetics and pharmacokinetic modeling, physiology-based pharmacokinetic models, concentration-effect relationships, pharmacodynamic model structures, practical model development strategies and model evaluation, applying models using simulations. Hands-on exercises will include the critical assessment of a PK-PD modeling paper and fitting a population PK model in R.
Obtain understanding of the most commonly used types of quantitative modeling approaches in pharmacology.
Learn how to choose the most relevant quantitative modeling strategy to address a particular pharmacological question given the availability of prior knowledge or data.
Develop an ability to understand and critically review quantitative modeling reports (e.g., publications),
Obtain basic understanding in conducting common quantitative model-based analyses.
Obtain understanding of the principles and analysis of differential equations in pharmacology.
The course is taught in March/April 2022. The specific schedule will be published on Brightspace.
Mode of instruction
The course will mainly consist of lectures and hands-on exercises. Active participation in the discussions and self-study skills are required for this course.
Written Exam (75%), and assignments (25%). The minimum average grade to pass this course is 6 out of 10.
Will be announced during the course.
Application via uSis. Registration closes 14 days before the start of the course.
Coordinator: Dr. J.G.C. van Hasselt (firstname.lastname@example.org).
A minimum of 10 participants is required, with a maximum of 25 students. Placement is based on the registration date.
This information is without prejudice. Alterations can be made for next year.