ÐÂÏã¸ÛÁùºÏ²Ê¿ª½±½á¹û

Summary

Pharmacometrics, a vital part of drug development and clinical pharmacology, is the mathematical study of the relationship between a treatment’s administered dose, its concentration in the body, and its measured effect, and how these evolve with time. This module will cover the theoretical underpinnings of pharmacometrics and provide computer laboratory hands-on data analysis experience. The module aims to equip you with an understanding of the biological basis of pharmacokinetic-pharmacodynamic processes, and also understand and apply the mathematical and statistical models necessary to describe these. You should be well equipped for further postgraduate study in pharmacometrics, or employment in the pharmaceutical industry. Ìý

Learning Objectives and Outcomes

After taking this module, you should be able to:

1. Understand the biological basis of pharmacokinetic and pharmacodynamic models, and be familiar with a number of model types
2. Understand the rationale behind using nonlinear mixed effects models
3. Know how to design a pharmacokinetic experiment (number of subjects, number of samples per subject) to be analysed with nonlinear mixed effects modelling
4. Know how to write the mathematical and statistical model for a nonlinear mixed effects model and how to code this in R.
5. Correctly use the terms: variable, parameter and covariate
6. Be able to write simple pharmacokinetic-pharmacodynamic models in closed form and as differential equations
7. Appropriately organise data for and read output from nonlinear mixed effects models using R
8. Analyse data arising from a pharmacokinetic-pharmacodynamic experiment using R

Who is this module for?

Students studying personalised medicine, pharmacy or pharmacology and therapeutics and wishing to learn quantitative methods. Medical statistics students wishing to learn an important application of statistical modelling relevant to the pharmaceutical industry.