Chapter
Chapter 1: Accelerated Predictive Stability: An Introduction
1. Historical Context of Accelerated Predictive Stability (APS)
2. General Principles of APS
3. Extent of APS Applications
4. Areas of APS Applications
4.1. Applications During Clinical Development
4.1.1. Fast comparative stability assessment of API salt form and polymorph
4.1.2. Fast stability rank order of prototype formulations
4.1.3. Support API and formulation process development
4.1.4. Packaging selection
4.1.5. Excursion evaluation
4.1.6. Predict drug substance retest period and clinical supply use period
4.1.7. Other applications
4.2. Applications for Registration
4.3. Applications for Postapproval Changes
Chapter 2: Regulatory Expectations and Industry Practice on Stability Testing
2. Regulatory Expectations for Stability Studies During Clinical Development
2.1. Goals and Issues for Clinical Stability
2.2. GMP for Clinical Stability Studies
2.3. Gaining Product Knowledge During Clinical Stability Testing
2.4. Stability Requirements for Phase 1 to Phase 3
2.5. Storage Conditions and Time Points for Stability Studies During Clinical Development
3. Registration Stability
3.1. Overarching Principles for Minimum Data Requirements
3.3. Postapproval Stability
3.3.1. Commitment to stability during product life cycle
3.3.2. Postapproval change stability packages
4. Alternative (e.g., APS) and Lean Stability Strategies Throughout the Product Life Cycle
4.1. Introduction to Lean Stability (Colgan et al., 2015)
4.2. Lean Approaches in Clinical Development
4.3. Lean Approaches at Registration
4.4. Lean Approaches for Line Extensions and for Postapproval Changes
4.5. The Global Regulatory Reception to Lean Strategies and a Path Forward
Chapter 3: Theory and Fundamentals of Accelerated Predictive Stability (APS) Studies
2. Factors That Affect Degradation Rate
2.3. Modeling the Combined Effects of Temperature and Humidity
2.3.1. Model A: Degradation rate increases exponentially with relative humidity
2.3.2. Model B: Degradation rate increases with humidity ``raised to a power´´
3. Measuring the Rate of Degradation (k)
3.1. Linear Degradation Model
3.2. Nonlinear Degradation Profiles
3.2.1. Nonlinear degradation profiles: Applying a kinetic model
3.2.2. Nonlinear degradation profiles: ``Shape parameter´´ approach
3.2.2.1. Sigmoidal and exponential kinetics
3.2.3. Nonlinear degradation profiles: ``Isoconversion´´ (or ``time to failure´´) methods
3.2.3.1. Methods for determining tiso
3.2.3.2. Methods for interpolation and extrapolation
4. Accelerated Predictive Stability (APS) Study Design
4.1. Selecting the Number of Different Storage Conditions to be Evaluated
4.2. Selection of Temperature and Humidity Conditions
4.3. Selection of Stability Durations and Timepoints
4.4. Practical Considerations for Fixed Humidity Stability Studies
4.4.1. The use of saturated salt solutions to control humidity
4.4.2. The case for measuring water activity
4.4.3. APS protocol design: Putting it all together
4.4.3.1. Example protocol type 1
4.4.3.2. Example protocol type 2
4.4.3.3. Example protocol type 3
5. Basic Data Processing to Provide a Shelf-Life Prediction
6. Assessing Goodness of Fit
7. The Temperature- and Humidity-Sensitivity Coefficients (Ea, B, and n1) in Context
7.1. Temperature Sensitivity (Ea)
7.2. Moisture Sensitivity (B or n1)
Chapter 4: Practical Considerations
2. Evaluation of Material Attributes
2.3. Glass Transition and Crystallization of Amorphous Drugs
2.4. Hydration and Dehydration of Crystalline Solids
2.5. Considerations on Other Material Attributes
3.1. Temperature and Relative Humidity Limits
3.3. Number of Storage Conditions, Time Points, and Repeats
3.3.3. Comprehensive approach
4.1. Use of Saturated Salt Solutions
4.2. Use of T/RH Stability Chamber
4.3. Sample Storage and Pull Schedule
5.1. Suitability of Test Methods
7. Determine Relative Humidity Within Packaged Product
Chapter 5: The Humidity Exposure of Packaged Products
2. Overview of the Humidity Modeling Procedure
3. Obtaining a Starting Point for RH in the Simulation
3.1. Estimation of the Starting ERH Level
3.2. Measurement of Water Activity
3.3. Measurement of Water Content
4. Moisture Permeability of Packaging
4.1. Moisture Vapor Transmission Rate (MVTR)
4.2.2. Multiple packaging layers
4.2.3. Heat induction seals (HIS) for bottles
4.2.4. Estimating the permeability of bottles of different sizes
5. Moisture Sorption Properties of the Packaging Contents
5.2. Drug Products, Desiccants, and Fillers
5.3. Moisture Sorption ``Isotherm´´ for the Entire Packaging Contents
5.3.1. Calculation of GAB parameters for multicomponent systems
5.4. Sorption, Desorption, and Hysteresis
5.5. Effect of Temperature on Moisture Sorption Isotherms
5.6. Calculating the New of Water Activity of Products in Presence of Desiccants
6.1. Simulating Multiple Packaging Layers
6.2. Simulating the Effects of User-Intervention Events
6.2.1. Opening a container: Air exchange
6.2.2. Opening a container: The permeability of HIS bottles
6.2.3. Removing product or desiccant
6.2.4. Adding or refreshing desiccant
7. Comparison of Simulated Versus Measured Humidity Profiles
8. Applications of Packaging Simulations
8.1. Predicting Chemical Degradation Rate of Packaged Products
8.1.1. Understanding the shapes of degradation curves of packaged products (case study)
8.3. The Effect of Bottle Count
8.4. Simulation of In-Use Scenarios
8.5. Assessing the Stability Risks of Humidity Excursions
8.6. The Effect of ERH on Other Potential Shelf Life-Limiting Attributes
Chapter 6: Data Evaluation and Statistical Methods
1.1. Scope of Evaluations
1.2. Treatment of Experimental Data
2. Experimental Designs for APS Studies
3.2. Model-Fitting Strategies Evaluated
3.2.1. Accelerated shelf-life model
3.2.2. Shelf-life model using time-scale least-squares regression
3.2.3. Classical kinetic model with unweighted second stage
3.2.4. Common intercept kinetic model with unweighted second stage
3.2.5. Classical kinetic model with weighted second stage
3.2.6. Common intercept kinetic model with weighted second stage
3.2.7. Extended nonlinear regression model
3.3. Effect of Data Censoring and Rounding on Estimating Shelf Life From APS Experiments
3.3.3. Results of model fitting
3.3.4. Effect of varying initial degradant concentration, temperature, and moisture sensitivity
Chapter 7: Strategies for Improving the Reliability of Accelerated Predictive Stability (APS) Studies
2. Changes in the Physical State of the Sample
2.1. Changes in Solid Form
2.1.1. Polymorph conversion
2.1.2. Hydration/Dehydration
2.1.3. Salt disproportionation or salt formation
2.1.4. Cocrystal breakback or formation
2.1.5. Process-induced disorder/amorphous content
2.1.8. Evaporation and sublimation
3. Useful Physical Property Characterization Techniques
3.1.1. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA)
3.1.2. Isothermal microcalorimetry
3.2. Powder X-Ray Diffraction (PXRD)
3.3. Dynamic Vapor Sorption (DVS)
3.4. Near-Infrared Spectroscopy (NIR) and Raman Spectroscopy
3.5. Microscopy—Optical Microscopy (OM) and Atomic Force Microscopy (AFM)
3.6. Small- and Wide-Angle X-Ray Scattering (SWAXS)
3.7. Solid-State NMR (SSNMR) Spectroscopy
4. Multiple Conversion Processes
4.1. Competitive Degradation Processes
4.2. Reversible Degradation Processes
4.3. Consecutive Degradation Processes
4.3.1. Temperature and humidity affects the rates of both steps equally
4.3.2. Temperature and humidity have unequal effects on the rates of Steps 1 and 2
4.4. Complex Degradation Processes
5. Problems Detected During Data Processing (Model Assessment)
5.1. Non-Arrhenius Effects of Temperature
5.2. Irregular Effects of Humidity
5.2.1. Increasing humidity decreases the degradation rate
6. Experimental and Analytical Variability
6.1. Analytical Method Uncertainty
6.2. Other Sources of Experimental Variability
6.2.1. Duration of exposure
6.2.2. Temperature and humidity control
6.3. Protocol Design and Sampling Strategies for Improving Prediction Accuracy
Chapter 8: Integration of APS Into a Rapid, Early Clinical Drug Product Development Paradigm
2. Drug Product Development Without a Standard Approach or APS Testing
3. A More Efficient Early Drug Product Development Process
3.1. A FAST Approach to Drug Product Development
3.1.1. Dry granulation as a standard process
3.1.2. Platform formulations
3.1.2.3. Application of default formulations
3.2. Application of the FAST Approach
3.2.1. APS study for FAST
3.3. The Impact of APS Stability Testing on the FAST Process
3.4. Nonstandard Excipients
4.1. BCS I Compound—Nearly a Placebo Formulation
4.2. BCS I/II Compound—An Example of Moderate Drug Loading
4.3. BCS II Compound—Amorphous Polymer-Based Dispersion Example
5. Shortcomings of APS Model
Chapter 9: Accelerated Predictive Stability (APS) Regulatory Strategies
3. Case Study 1A: Example of CTA Strategy: Use of APS Data Alone to Underwrite an Initial Use Period Assignment for an Im ...
4. Case Study 1B: CTA Strategy: The Use of APS Approaches to Assess Impact of Change in Drug Substance Synthetic Route
5. Case Study 1C: The Use of APS Data to Support Stability-Related CTA Queries
6. Initial Marketing Registration and Postapproval Change Submissions
7. Case Study 2A: The Use of APS Studies to Assess the Stability of Drug Product Manufactured With Drug Substance Contain ...
8. Case Study 2B: APS Studies to Support Proposed Commercial Packaging and Potential Future Changes
9. Case Study 2C: The Use of APS Studies for the Selection of Drug Product Composition
10. Additional Potential Opportunities
Chapter 10: Embedding APS Within Business
1. Introducing Change in a Culture of Risk Aversion
2. Current Stability Practices Throughout the Development Process and Associated Gaps/Risks
3. The Perceived Risk of APS
4. Reframing APS as a Risk Mitigation Strategy
6. Develop an Implementation Roll-Out Approach
7. Construct a Business Process
7.2. Execute the Stability Protocol
7.3. Build Stability Models
7.4. Interrogate the Models/Outcomes
Chapter 11: Implementing an Accelerated Predictive Stability Program
1. Overview and Background
2. Implementing an Accelerated Stability Assessment Program
2.2. Integrating ASAP With Package Modeling to Predict Product Stability
2.3. General Process Flow
2.4. Study Execution Considerations
2.4.1. Sample equilibration
2.4.3. Sample equilibration approaches
2.4.3.1. Option A: Equilibrate sample at desired temperature in a temperature- and humidity-controlled oven
2.4.3.2. Option B: Equilibrate sample at desired temperature inside desiccator with saturated salt solutions
2.4.3.3. Option C: Equilibrate sample at room temperature in foil bags in desiccator with saturated salt solution, seal, ...
3. Continuous Improvement
3.2. Process Improvements
4.1. Drug Substance, Starting Materials, and Intermediates
4.2.1. Lyophilized drug product
4.2.2. Solid oral drug product
Part II: Industry Practices
Chapter 12: Accelerated Stability Assessment Program (ASAP) Applications in a Postapproval Environment
2. Case Study 1: Investigating OOS Stability Issues
2.1. Prediction of Packaged Drug Products
2.3. Predictive Stability Assessment of Various Formulations
3. Case Study 2: Amlodipine Besylate Tablet ASAP Study
3.1. Proposed Package Change
4. Case Study 3: Changes in Packaging Configuration Using ASAP
4.1. Proposed Package Change
Chapter 13: ASAP Application: Unstable Drug Candidate in Early Development
2. Drug Substance Stability Assessment
2.1. Estimation of API Initial Retest Period
2.2. Comparison With Actual ICH Stability Data
3. Drug Product Stability Assessment
3.1. ASAP Assessment of Powder for Oral Solution (PfOS) Prototype Formulations
3.1.1. Selection of capsule shell for PIC assessment
3.1.2. Effect of excipients and capsule shell on PfOS shelf life
3.2.1. Assessment of effect of process on tablet stability
3.2.1.1. Effect of coating agent
3.2.1.2. Effect of mixing process
3.2.2. Assessment of prototype tablet formulations of common excipients
3.2.3. Assessment of basic stabilizers in prototype tablet formulations
Chapter 14: ASAP Application in Suspension, Liquid, Lyophilized, and Controlled-Release Drug Products
2.1. Stress Stations With Temperature/Humidity Control and Recording
2.2. Analysis of ASAP Samples
2.3. Data Analysis and Modeling
3. Results and Discussion
3.1. Evaluation of In-House Stress Stations
3.2. Compound A: Suspension Formulation
3.3. Compound B: Liquid Formulations
3.4. Compound C: Lyophilized Formulation
3.4.1. Drug substance ASAP study
3.4.2. Prelyophilization solution ASAP study
3.4.3. Lyophilized formulation ASAP study
3.5. Compound C: Controlled-Release Matrix Tablet
Chapter 15: Applications of ASAP to Generic Drugs
Chapter 16: ASAP Application: Nicotine Lozenges
2. Accelerated Stability Study Design
3. Moisture Sorption Isotherm
5. Isoconversion Point (Pi) Estimation
7. ASAPprime® Shelf-Life Prediction and the Actual Shelf-Life Calculation
8. Discrepancy Between the Predicted and Actual Shelf Lives
Chapter 17: ASAP Applications in Clinical Development: Prediction of Degradation and Dissolution Performance
2. Prediction of Initial Shelf Life
2.1. Experimental Conditions for Initial Shelf-Life Estimation
2.2. Results and Discussion
3. Prediction of Dissolution
3.1. Experimental and Methods for Dissolution Prediction
3.1.1. Accelerated experimental conditions
3.1.2. Dissolution methods
3.2. Results and Discussion
3.3.1. Dissolution modeling hypothesis
3.3.4. Predicted probability of passing specification at the end of shelf life
3.3.5. Predicted %dissolved at the end of shelf life
3.4.1. Tablet water content in packaged product on stability
3.4.2. Verification of predicted %dissolution change with real-time stability data
Chapter 18: Accelerated Predictive Stability (APS) Applications: Packaging Strategies for Controlling Dissolution Performance
1.1. Dissolution as a Critical Quality Attribute
1.2. Temperature and Humidity Influence on Drug Release
2. Humidity Changes in Packaging
2.1. Role of Packaging on Moisture Protection
2.2. Effect of Product Sorption on RH in Packaging
2.3. Effect of Desiccant on RH in Packaging
2.4. Predicting RH for Packaged Product
3. Example of IR Tablets With High-Humidity Sensitivity
3.2. Manufacturing of Tablets
Chapter 19: Accelerated Stability Modeling: Investigation of Disintegration Time of a Drug Product With Sodium Bicarbonate
2. Primary Accelerated Stability Study Experimental Design
3. Accelerated Stability Data
4. Analysis of Drug Product Z Data
5. Prediction of Long-Term Disintegration Time for Drug Product Z
Chapter 20: Accelerated Stability Modeling: An Ionic Liquid Drug Product
3.1. Experimental Methodology
3.2. Analytical Methodology
4.1. Discussion of Chromatographic Results
5. Analysis and Modeling of Data
5.1. Analysis of the Glutaric Acid Formulation
5.2. Analysis of the Lactic Acid Formulation
5.2.2. N-oxide degradation product
5.2.3. RRT 0.51 degradation product
5.2.4. RRT 0.72 degradation product
5.2.5. RRT 0.84 degradation product
5.2.6. RRT 0.90 degradation product
5.2.7. RRT 0.97 degradation product
5.2.8. ``Deg9´´ degradation product
5.2.9. RRT 1.22 degradation product
5.2.10. RRT 1.35 degradation product
5.2.11. RRT 2.02 degradation product
6. Discussion and Optimization of Storage Conditions for the Lactic Acid Formulation
Chapter 21: Accelerated Stability Modeling: Assay Loss of Nicotine Lozenges
2. Experimental Design for Accelerated Stability Study
3. ASM Analysis of Accelerated Stability Data
3.1. Linearization of Sigmoidal Degradation Profiles
4. Comparison of APS Predictions to Long-Term Storage Data
5. Comparison of Prediction Results to ASAPprime®
Chapter 22: Accelerated Stability Modeling: Desolvation of a Solvate Drug Product
2. Experimental Design for Drug Product ``M´´ ASM Study
3. Analysis of Drug Product ``M´´ Data
4. Comparison of Short-Term ASM Model to Long-Term Storage Data
Accelerated Predictive Stability (APS)
：Fundamentals and Pharmaceutical Industry Practices
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