The course introduces 'classical' statistical design of experiments, particularly designs for blocking, full and fractional factorial designs with confounding, and response surface methods. Topics covered include (restricted) randomization and blocking, sample size and power calculations, confounding, and basics of analysis-of-variance methods for analysis including random effects and nesting.

This course introduces how Modelling and Simulation (=mathematical modelling) is applied today for the development of novel drugs in the pharmaceutical industry. Background lectures are combined with hands-on exercises on real-world examples.

The seminar explores computational and modeling techniques for biology and biomedicine. These include dynamic systems, control theory, machine learning, mixed effects models, and pharmacometrics. Each student conducts a literature study on a relevant topic chosen in agreement with the supervisor, critically appraises the literature/methods and presents findings in an oral presentation.