# Understanding Design of Experiments (DOE)

### This is how your training course could look like:

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Please note that we need about 3 months preparation for the organisation of your in-house training course.

## A course about the basics of DOE with practicing of factorial and fractional DOE with a software program (e.g. Minitab 19)

Below is an example of an inhouse training course. This course can be offered as a 2 day or 3 day training.

This course will explain the basics of DOE with practicing with factorial and fractional DOE as well as DOE by RSM and DOE of mixtures of drug ingredients. If you have no or little previous knowledge with DOE, you will learn how to set up an experimental design and how to explore the effect of factors that influence either a development/production process or an analytical method while taking into account interactions between the factors.

• Introduction
• DOE and Quality-by-Design
• Regulations (EU and FDA)
• A factorial experiment
• DOE vs One-at-a-Time experiment
• Where is DOE applied in development and validation of analytical methods
• Where is DOE applied  in process development and validation
• DOE by hand calculations: effects and interactions
• Factorial Experiments (categorical and numeric factors)
• Two and three factorial designs
• Manual calculation of main effects
• Manual calculation of interactions
• What is an orthogonal DOE
• Exercises with Excel
• Acquaintance with Minitab
• Basic structure of Minitab software
• Input of data
• Running a DOE
• Plotting  output results
• Practicing with Minitab
• Basic statistical tools for interpretation of DOE output
• F-test
• t-Test
• Anova
• Multiple linear regression
• Diagnostics for goodness of fit to model
• Exercises with Excel
• Are the coefficients significant?
• Deviations from normality plot
• Making replicate experiments
• Adding experiments at center points
• Using known variability
• Exercises with Excel
• Full Factorial DOE experiments with Minitab
• Two factor full DOE experiments
• Interactions between two factors
• Plotting Main effects and Interactions
• Interpretation of DOE Minitab output
• Does the linear fit the model?
• Significance of p values
• General full factorial DOE
• Exercises with Minitab
• Exercises in interpretation of Minitab outputs
• Screening design experiments with Minitab
• Two and three factor experiments with Minitab
• Aliasing in DOE experiments
• Resolution of  DOE experiment
• 4-7 fractional factorial DOE
• Plackett-Burman designs
• Definitive screening design
• Exercises with Minitab:
• a. Robustness of HPLC method with fractional DOE
•  b. Optimisation of a process with fractional DOE
• Strategy of DOE in drug development process
• Screening experiments
• Fractional experiments
• Full Factorial experiments
• Optimization experiments: surface Response Methodology
• Design space
• Normal operating range (NOR)
• Robustness experiments of a process/method
• Optimization with Response Surface Methodology
• 22 factorial experiments with RSM
• Contour plot
• Surface plot
• Concept of Design space
• Exercises: optimization of drug solubility with RSM design, Effect of process parameters  on dissolution assay and variability
• Design of mixtures
• Types of designs
• Interpretation of Minitab output
• Exercise: Effect of mixtures of excipients on tablet hardness

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