SFKKIF102U Design and Analysis of Experiments

Volume 2021/2022
Education

MSc Programme in Medicinal Chemistry - elective

MSc Programme in Pharmacy (Danish programme cand.pharm) - elective

MSc Programme in Pharmaceutical Sciences (Danish programme cand.scient.pharm) - restricted elective

MSc Programme in Pharmaceutical Sciences (English programme) - restricted elective

Content
  • 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.

Learning Outcome

At the end of the course, students are expected to be able to:

Knowledge

  • use and interpret output from the statistical computer software R.

 

Skills

  • carry out statistical analysis of data obtained from a given experimental design, most often using regression analysis techniques.
  • present and interpret the results obtained from an experimental design.

 

Competences

  • design relevant experimental work to support the lifecycle phases of a new pharmaceutical product: discovery, development, production and quality control.
  • judge the necessary amount of experimentation, take into account practical restrictions and anticipate and prevent/mitigate sources of the types of bias often encountered during these phases.

Design and Analysis of Experiments, D. C. Montgomery, 7. ed., 2009.

Lecture notes are available from the course homepage.

Teaching is based on the assumption that the students have acquired knowledge, skills and competences corresponding to those obtained by completion of the first five semesters of the BSc Programme in Pharmacy.
Lectures/seminars: 33 hours
Classroom exercises: 18 hours
  • Category
  • Hours
  • Lectures
  • 33
  • Class Instruction
  • 18
  • Preparation
  • 151
  • Exam
  • 4
  • Total
  • 206
Continuous feedback during the course of the semester
Credit
7,5 ECTS
Type of assessment
Written examination, 4 timer under invigilation
The written examination is a two-part questionnaire. The first part is an essay-type, practical question asking the student to partially design an experiment and/or do a statistical analysis. The second part is a multiple-choice test with questions generally related to important issues discussed in the course. Compared to the bachelor level examination, this exam contains more questions both in the essay part and the multiple-choice test part.
Aid
Written aids allowed

There is access to the following at the exam on Peter Bangs Vej:

  • MathType - formel programme
  • Maple
  • Latex
  • LYX (Latex formel editor)
  • R and R studio
  • Digital Notes (It is allowed to upload notes for the ITX exam via digital exam. You will find a link to this feature from your exam in Digital Exam).

Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assesment

To achieve the grade 12 the student must be able to:

Knowledge

  • use and interpret output from the statistical computer software R.
  • discuss statistical quality control

 

Skills

  • carry out statistical analysis of data obtained from a given experimental design, most often using variance and regression analysis techniques.
  • present, perspective and interpret the results obtained from a experimental design.

 

Competences

  • independently design relevant experimental work to support the lifecycle phases of a new pharmaceutical product: discovery, development, production and quality control.
  • judge the necessary amount of experimentation, take into account practical restrictions and anticipate and prevent/mitigate sources of the types of bias often encountered during these phases.