Statistical Design of Experiments in the Pharmaceutical Industry
6/7 October 2026
Course No. 23040
Speakers
Dr Christian Palmes
Bayer AG
Highly Interactive Training: Hands-on Exercises and Guided Minitab Sessions
- Plan and analyze pharmaceutical DoE case studies using Minitab
- Understand main effects and interactions using Excel calculations
- Optimize processes and derive Design Spaces using Response Surface Methodology
- Guidelines covered: ICH Q8, Q11, Q14 and Pharm. Eur. Supplement 11.7
Target Group
This course is intended for employees in development, quality control laboratories, process engineering and quality assurance who currently use DoE or plan to apply it in the future. It is also suitable for GMP auditors, inspectors and validation personnel involved in reviewing DoE studies or regulatory submissions. A basic understanding of statistics is helpful, but no advanced statistical knowledge is required.
Remark: The number of participants is limited to ensure effective hands-on training.
Objectives
This DoE course offers a clear, hands-on introduction to planning and analyzing experiments using Minitab. It features four pharmaceutical case studies presented in a fully guided, step-by-step format.
DoE theory is covered at a practical level, enabling participants to understand the key concepts, interpret software outputs correctly and draw sound conclusions from experimental data.
Day 1 focuses on the planning stage of DoE
Day 2 focuses on the analysis of DoE results
The course covers a broad range of classical and modern DoE designs, including full and fractional factorial, Plackett-Burman, central composite (RSM), D-optimal and mixture designs.
Background Design of Experiments (DoE) is a key statistical methodology in Quality by Design (QbD). It supports the systematic investigation of process parameters and quality attributes, helps identify critical factors and provides a scientific basis for defining robust operating ranges and Design Spaces in line with regulatory expectations.
Programme
Day 1
Welcome and Course Introduction
Short round of introductions
Objectives of the training
Principles of DoE Planning: Part I
General considerations – why DoE?
OFAT (One-Factor-at-a-Time) versus DoE
The DoE workflow
Experimental goals
Main, interaction and quadratic effects
Introductory Example: Optimizing a Cake Recipe
Get familiar with DoE in Minitab
Plan and evaluate a factorial experiment in Minitab
Understand main and interaction effects using Excel calculations
Principles of DoE Planning: Part II
Randomization, blocking, replication and center Points
Power, sample size and orthogonality
Fractional factorial designs: resolution III, IV and V
Plackett-Burman and central composite designs
Special designs: D-optimal, I-optimal and mixture designs
Case Study: Filtration Rate Optimization: Planning
Plan a full-factorial design in Minitab
Assess signal-to-noise ratio, correlation and effect sizes
Use Minitab’s DoE planning tool
Hands-on Exercise: Planning a DoE Study
Plan a DoE on your own
Case Study 1: Optimization of a granulation process
Case Study 2: HPLC robustness assessment
Day 2
Building and Assessing Statistical Models
Effect selection
Analysis of variance (ANOVA)
Model building and interpretation
Statistical significance, p-values and model terms
Confidence, prediction and tolerance intervals
Data and model visualizations with Minitab
Model-Based Prediction, Design Space, and ICH Q8
Goodness of fit and predictive performance
Lack-of-fit and curvature
Predicted values and residuals
Transformations (Box-Cox)
Case Study: Filtration Rate Optimization: Analysis
Effect selection for model building
Interpretation of model diagnostics
Derivation and assessment of the Sweet Spot and Design Space
Hands-on Exercise: DoE Analysis
Analyze the HPLC or granulation DoE case study
Derive a Sweet Spot and Design Space in line with ICH Q8
Supplementary Material: Design Augmentation
Questions and elaborated sample Solutions
Simultaneous optimization of three responses with two factors
Design augmentation to incorporate quadratic effects
Circumscribed central composite designs in Minitab
Design Space and Sweet Spot derivation using overlay plots
Further Information
Technical Requirements Our live online training courses and webinars are conducted using Webex. At www.gmp-compliance.org/training/online-training-technical-information you will find all necessary information for participation, including a system check to verify whether your IT environment meets the technical requirements. If the installation of browser extensions is restricted due to internal IT policies, please contact your IT department. Webex is widely used, and installation is straightforward.
Fees (per delegate, plus VAT) ECA Members EUR 1,890 APIC Members EUR 1,990 Non-ECA Members EUR 2,090 EU GMP Inspectorates EUR 1,045 The conference fee is payable in advance upon receipt of invoice.
Supplementary Material: Participants will receive an additional DoE case study as homework to reinforce the course content.
Pre-requisites: Each participant should have access to a computer with current versions of Excel and the desktop version of Minitab installed. A time-limited free trial of Minitab is available from http://www.minitab.com. The software should be downloaded and tested a few days before the course starts to ensure that it works properly.
Presentations/Certificate The presentations for this event will be available for you to download and print before and after the event. After the event, you will automatically receive your certificate of participation.
Conference language The official conference language will be English.
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