Session 3: DoE Implementation

Hands-on Training in Design of Experiments for Formulation Development

Master practical DoE skills through real pharmaceutical case studies and step-by-step implementations

Session Progress

Session 3 of 3 - DoE Implementation & Optimization

Learning Objectives

By the end of this session, you will be able to:

DoE Fundamentals Review

Step-by-Step Reasoning: Why DoE Works

Let's think about this step-by-step:

  1. Understanding the Problem: Traditional one-factor-at-a-time (OFAT) experiments miss interactions between factors
  2. DoE Solution: Factorial designs systematically vary multiple factors simultaneously
  3. Information Gain: We obtain main effects + interactions + statistical significance
  4. Efficiency: More information per experiment compared to OFAT

💊 Pharmaceutical Example: Tablet Optimization

Scenario: Optimizing a tablet formulation for dissolution rate

Step-by-Step Approach:
  1. Identify Factors:
    • A: Binder concentration (2-6% w/w)
    • B: Compression force (5-15 kN)
    • C: Disintegrant level (1-3% w/w)
  2. Define Response: Dissolution at 30 minutes (% dissolved)
  3. Select Design: 2³ factorial design (8 experiments)
  4. Randomize Run Order: Essential for validity
Run Binder (A) Force (B) Disintegrant (C) Dissolution (%)
1-1 (2%)-1 (5kN)-1 (1%)65.2
2+1 (6%)-1 (5kN)-1 (1%)58.7
3-1 (2%)+1 (15kN)-1 (1%)52.4
4+1 (6%)+1 (15kN)-1 (1%)48.9
5-1 (2%)-1 (5kN)+1 (3%)78.1
6+1 (6%)-1 (5kN)+1 (3%)71.6
7-1 (2%)+1 (15kN)+1 (3%)68.3
8+1 (6%)+1 (15kN)+1 (3%)64.7

Effect Calculation - Step by Step

Let's calculate the main effect of Binder concentration (A):

Effect A = (Average response at high level) - (Average response at low level)

Step 1: Identify high level runs (+1): Runs 2, 4, 6, 8

Step 2: Calculate average: (58.7 + 48.9 + 71.6 + 64.7) / 4 = 60.975%

Step 3: Identify low level runs (-1): Runs 1, 3, 5, 7

Step 4: Calculate average: (65.2 + 52.4 + 78.1 + 68.3) / 4 = 66.0%

Step 5: Calculate effect: 60.975 - 66.0 = -5.025%

Effect of Binder = -5.025%
Interpretation: Increasing binder from 2% to 6% decreases dissolution by 5.025%

Practical Tools & Software

Microsoft Excel

Data Analysis ToolPak for ANOVA, regression analysis, and basic DoE calculations

Recommended for: Beginners

R Statistical Software

Advanced DoE packages: FrF2, rsm, AlgDesign for complex experimental designs

Recommended for: Advanced users

Python

Libraries: scipy, statsmodels, pyDOE2 for experimental design and analysis

Recommended for: Programming enthusiasts

Online DoE Tools

Web-based calculators for factorial design generation and analysis

Recommended for: Quick calculations

Practical Exercises Overview

Exercise Structure

Each practical exercise follows our step-by-step reasoning approach:

  1. Problem Definition: Clear statement of formulation challenge
  2. Factor Identification: Critical material attributes and process parameters
  3. Design Selection: Appropriate DoE design with justification
  4. Data Collection: Realistic pharmaceutical data
  5. Analysis Execution: Step-by-step statistical analysis
  6. Interpretation: Practical significance and decision making
  7. Optimization: Finding optimal conditions
  8. Validation: Confirmation experiments

💊 Case Study Preview: Extended Release Tablet Development

Challenge: Develop an extended-release tablet with target 12-hour drug release profile

Critical Quality Attributes (CQAs):
  • Drug release at 2 hours: 15-25%
  • Drug release at 8 hours: 55-75%
  • Drug release at 12 hours: ≥80%
  • Tablet hardness: 80-120 N
Critical Material Attributes (CMAs):
  • HPMC concentration (10-30% w/w)
  • Compression force (8-20 kN)
  • Granulation time (5-15 minutes)

Design Approach: Central Composite Design (CCD) for response surface modeling and optimization

Pre-Session Preparation

Essential Prerequisites

  • Completed Module 4: DoE Design Studio theory
  • Understanding of factorial designs and ANOVA
  • Basic Excel skills (formulas, charts, regression)
  • Pharmaceutical formulation fundamentals

Materials Needed

  • Computer with Excel or statistical software
  • DoE practice datasets (provided)
  • Scientific calculator
  • Note-taking materials

Session Timeline

1

Factorial Analysis Practice (60 minutes)

Design and analyze 2³ factorial experiment for tablet optimization

2

Response Surface Methodology (75 minutes)

Build response surface models and optimize formulation conditions

3

Solution Review & Discussion (30 minutes)

Compare results, discuss alternative approaches, and address questions