Introduction to Quality by Design in Pharmaceutical Manufacturing and Analytical Development (AAPS Introductions in the Pharmaceutical Sciences, 10)

✍ Scribed by Márcia Cristina Breitkreitz (editor), Hector Goicoechea (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 268
• Category: Library

✦ Synopsis

Written by twenty-five authors from academia, pharmaceutical industry and Pharmacopeias worldwide, this monograph covers the fundamentals and applications of Quality by Design (QbD) and Analytical Quality by Design (AQbD) in a practical and didactic manner. The book starts by describing the motivation and the urgent need for the implementation of the QbD framework in pharmaceutical development, along with the definition of its major elements: Quality Target Product Profile (QTTP), Critical Quality Attributes (CQAs), Critical Process Parameters (CPPs), Critical Material Attributes (CMAs) and the importance of using multivariate methods of Design of Experiments (DOE). The concept of life cycle and regulatory perspectives are discussed.

Three chapters are entirely dedicated to DOE theory from screening to optimization designs. Moreover, a comprehensive discussion on modelling and data treatment is presented. Practical aspects of QbD and DOE for pharmaceutical product and process of different dosage forms is included, as well as a practical guide of the input process variables, material attributes, intermediate, and final quality attributes for the most representative pharmaceutical processes. Analytical Quality by Design (AQbD) is also deeply explored, including risk analysis, definitions of Analytical Target Profile (ATP), Method Operable Design Region (MODR) and the life cycle approach, taking into account the compendial and regulatory perspectives. A detailed example of a new chromatographic method for the quality control of a pharmaceutical topical product based on the AQbD procedure is shown.

Finally, advanced statistical approaches and DOE methods for extraction studies of bioactive compounds are also presented. The vast amount of information offered in this book provides a comprehensive perspective on QbD, AQbD and DOE principles, essential tools for modern pharmaceutical and analytical development.

✦ Table of Contents

Preface
Acknowledgments
Contents
Part 1: Quality by Design (QbD)
Chapter 1: Pharmaceutical Quality by Design (QbD) Overview and Major Elements
1.1 Introduction
1.2 QbD Elements
1.2.1 The Quality Target Product Profile (QTPP)
1.2.2 Global Critical Quality Attributes (CQAs)
1.2.3 Risk Analysis
1.2.4 Multivariate Analysis: Design of Experiments (DOE)
1.2.5 Design Space(s)
1.3 Control Strategy
1.4 Regulatory Aspects
References
Chapter 2: Fundamentals of Design of Experiments and Optimization: Designs for Factor Screening and Data Analysis in Pre-Respo...
2.1 Introduction
2.2 General Overview of RSM and Basic Terminology
2.3 Completely Randomized Designs for Factor Screening
2.3.1 Two-Level Full and Fractional Factorial Designs
2.3.2 Plackett-Burman Designs
2.4 Data Analysis in Pre-RSM
2.4.1 Graphical Analysis
2.4.2 Multiway ANOVA
2.5 Non-randomized Designs
2.5.1 Blocks
2.5.2 Split-Plot Designs
References
Chapter 3: Fundamentals of Design of Experiments and Optimization: Experimental Designs in Response Surface Methodology
3.1 Introduction
3.2 Response Surface Methodology Designs with Independent Factors
3.2.1 Symmetrical Designs
3.2.1.1 Full Factorial Design
3.2.1.2 Central Composite Design
3.2.1.3 Box-Behnken Design
3.2.1.4 Doehlert Design
3.2.2 Asymmetrical Designs: D-Optimal Design
3.2.3 Split-Plot Designs (SPD)
3.3 Response Surface Methodology Designs with Dependent Factors: Mixture Designs
3.3.1 Simplex Designs
3.3.2 Simplex Designs with Constraints in the Component Proportions: Pseudo-Components
3.3.3 Designs with Constraints in the Component Proportions When the Simplex Shape Has Been Lost: D-Optimal Criterion
3.3.4 Mixture-Process and Mixture-Mixture Designs
3.4 Desirable Properties of Response Surface Designs
References
Chapter 4: Fundamentals of Design of Experiments and Optimization: Data Modeling in Response Surface Methodology
4.1 Introduction
4.2 Multiple Linear Regression (MLR)
4.2.1 General Theory
4.2.2 Model Inference, Validation, and Diagnosis
4.2.3 Model Interpretation and Prediction
4.2.4 Mixture Experiments: The Scheffé Model
4.3 Artificial Neural Networks (ANNs)
4.4 Optimization
4.4.1 Multiple Response Optimization: The Desirability Function
4.5 Software
References
Chapter 5: Quality by Design in Pharmaceutical Product and Process Development
5.1 Raw Materials: A Quality by Design Point of View
5.2 How to Structure DOE Studies Within the QbD Framework
5.3 Quality by Design in Pharmaceutical Product and Process Development
5.4 Solid Dosage Forms
5.4.1 Direct Compression
5.4.2 Dry Granulation
5.4.3 Wet Granulation
5.4.4 Drying
5.5 Liquid and Semisolid Dosage Forms
5.6 Quality Attributes
References
Chapter 6: A Quality by Design Update on Nano-drug Delivery Systems
6.1 Introduction
6.2 Nanotechnology
6.3 Production of Nanostructures
6.4 Nanocrystals
6.5 Polymeric Nanoparticles
6.6 Liposomes
6.7 Conclusions
References
Chapter 7: Control Strategies of Solid Dosage Forms by PAT Tools
7.1 Introduction
7.2 Process Analytical Technologies
7.3 Near-Infrared Spectroscopy
7.4 Raman Spectroscopy
7.5 Microwave Resonance Technology (MRT)
7.6 Acoustic Emission (AE)
7.7 Terahertz Spectroscopy
7.7.1 Terahertz Time-Domain Spectroscopy (THz-TDS)
7.7.2 Terahertz Pulsed Imaging (TPI)
7.8 Data Analysis and Process Modelling
7.8.1 Model Development
7.9 Conclusion
References
Part 2: Analytical Quality by Design (AQbD)
Chapter 8: Analytical Quality by Design Fundamentals and Compendial and Regulatory Perspectives
8.1 Introduction to Analytical Quality by Design Principles
8.1.1 Compendial Perspectives on AQbD
8.1.2 Analytical Procedure Lifecycle Approach and AQbD Fundamentals
8.1.3 Regulatory Perspectives on AQbD
8.1.3.1 ICH Q14 Analytical Procedure Development
8.2 Analytical Target Profile (ATP)
8.3 Quality Risk Management
8.3.1 Quality Risk Management Principles and Framework
8.3.2 Risk Assessment
8.3.2.1 Initiating a QRM Process
8.3.2.2 Risk Assessment
8.3.3 Risk Control
8.3.4 Risk Communication and Review
8.3.5 Risk Management Tools
8.3.5.1 Basic Tools
8.3.5.2 More Advanced Tools
8.4 Analytical Procedure Development and Quality Risk Management
8.4.1 Intended Purpose of the Study and Quality Risk Management
8.4.2 Screening Studies
8.4.3 Optimization Studies
8.5 Robustness Assessment and Method Operable Design Region (MODR)
8.6 Replication Strategy and Analytical Control Strategies
8.6.1 Statistical Considerations and Uncertainty
8.7 Validation in the Analytical Procedure Lifecycle Framework
8.7.1 Stage 2: Analytical Procedure Performance Qualification (APPQ)
8.7.2 Protocol and Study Design
8.7.3 Results and Documentation
8.8 Ongoing Procedure Performance Verification and Analytical Procedure Lifecycle Management
8.8.1 Designing a Routine Monitoring Program
8.8.2 Identification of Analytical Procedure Aspects That Need Further Investigation During Routine Use
8.8.3 Tools Used by the Control Strategy
8.8.4 Tools Used for Trending
8.8.5 Procedure Performance Monitoring After Analytical Condition Changes
References
Chapter 9: Analytical Target Profile (ATP) and Method Operable Design Region (MODR)
9.1 Analytical Target Profile
9.2 Robustness Assessment and Method Operable Design Region (MODR)
9.2.1 Concept of Knowledge Space and Method Operable Design Region (MODR)
9.2.2 Risk Assessment and Control
9.2.2.1 Risk Assessment Based on Target Measurement Uncertainty (TMU)
9.2.2.2 Risk Assessment Based on Process Capability Assessment
9.2.3 Considerations for MODR Design and Validation
9.2.3.1 Changes Within the MODR
References
Chapter 10: Quality by Design Applications to Development of Analytical Methods for Quality Control of Pharmaceuticals
10.1 Introduction
10.2 Analytical Problem Statement
10.3 Analytical Target Profile
10.4 Technique Selection
10.5 Scouting Phase: Initial Procedure and Preliminary Experiments
10.6 Critical Method Attributes (CMAs)
10.7 Critical Method Parameters (CMPs)
10.8 Quality Risk Management
10.8.1 Risk Assessment
10.8.1.1 Risk Identification
10.8.1.2 Risk Analysis
10.8.1.3 Risk Evaluation
10.8.1.4 Risk Control and Risk Review
10.9 Design of Experiments. Response Surface Methodology
10.9.1 First-Order Designs
10.9.2 Second-Order Designs
10.10 Method Operable Design Region and Control Space
10.11 Optimal Working Point
10.12 Experimental Check
10.13 Method Validation
10.14 Control Strategy and Routine Monitoring
References
Chapter 11: Design of Experiments Applied to the Extraction of Active Compounds
11.1 Introduction
11.2 Choosing the Appropriate Solvent
11.3 Experimentation Strategy
11.4 Mixture Models
11.5 ANOVA Simultaneous Component Analysis
11.6 Principal Component Analysis
11.7 Application Section
References
Index