SFKKIF102U Design and Analysis of Experiments

• Introduction to statistical modeling and hypothesis testing.
• Useful experimental plans in pharmaceutical sciences.
• Principles of confounding, randomization, blocking and balancing.
• Choice of necessary sample size in setting up experiments.
• Estimation, testing and interpretation of treatment effects.
• Experiments with many factors and principle of interaction.
• Restrictions on randomization and elementary split plot and repeated measures designs.
• Principles of statistical quality control.

The syllabus is presented by three parallel activities. The theoretical and methodological content is covered in about 12 double lectures based on the textbook and lecture notes. Pharmaceutical applications and case studies related to the most important activities involving discovery and development of pharmaceutical products are presented in a series of about six double lectures. Training in the practical design and analysis of experiments is provided in a series of nine double classroom sessions, in which the different methods are discussed and practised using manual calculations and the statistical software R. In addition the students will hand in and present a written assignment.

The purpose of the course is to introduce a general statistical approach to the design of laboratory and similar experiments and to analyse the resulting data, including statistical quality control. Along with the statistical and methodological content of the course, a number of concrete and frequently used pharmaceutical applications (designed experiments) are presented. Examples are clinical trials (including e.g. crossover and repeated measures designs), toxicity testing, bio-equivalence analyses, assay validation, design and analysis of epidemiological surveys, etc. Regarding the statistical design of experiments, the main objective is to assure the accuracy and precision of the data so that reliable and reproducible conclusions can be drawn concerning the relations being studied.