How to Scale-Up a Wet Granulation End Point Scientifically

Michael Levin

• Publisher: Academic Press
• Year: 2015
• Print ISBN:
  9780128035221
• eBook ISBN:
  9780128035603
• Topic: Medicine
• Subtopic: Pharmacology

How to Scale-Up a Wet Granulation End Point Scientifically provides a single-source devoted to all relevant information on the scale-up of a wet granulation end point. Contents include a general description, problem identification, and theoretical background with supporting literature, case studies, potential solutions, and more. By outlining issues related to scale-up and end-point determination, and then using practical examples and advice to address these issues, How to Scale-Up a Wet Granulation End Point Scientifically is a valuable and essential resource for all those pharmaceutical scientists and technologists engaged in the granulation process. - Thoroughly referenced and based on the latest research and literature - Part of the Expertise in Pharmaceutical Process Technology Series edited by internationally respected expert, Michael Levin - Illustrates the most common problems related to scale-up of a wet granulation end point and provides valuable insights on how to solve these problems in a practical way

Chapter 1

Scale-Up Basics

Abstract

This introductory chapter defines the notions of scale-up and lays the foundation of the discussion that follows. It also indicates the distinction between developmental and postapproval scale-up requirements.

Keywords

scale-up; dimensional analysis; SUPAC

Scale-up is generally understood as the procedures of transferring the results of research and development obtained on a laboratory scale to the pilot plant and finally to production scale. Although many variations of the theme exist (e.g., batch size enlargement, scale down when required to improve the quality of the product, pilot scale as an intermediate step, multiplying small- or medium-scale operations to increase output), this book concentrates on classic procedures of size increase of the processing volume, specifically as applied to wet granulation.

Let’s face it, most scale-up practices and procedures currently used in the pharmaceutical industry are empirical in nature.

There are always some practical “trade secrets” that are known to experienced operators, some unwritten operating procedures that are not necessarily based on any theoretical foundation. The problem with this approach is that it is empirical and thus has limited applicability to ever-changing conditions.

Numerous drawbacks and difficulties could be met on this path of scale-up. When quality of the product on the production floor is not as was envisioned in the development and preapproval stages, losses in terms of effort and money can be enormous. That is why scale-up as part of development is so important and why postapproval changes are so strictly regulated.

No unit operation is exempt from this predicament, and wet granulation is one of the most challenging processes to scale-up because of many variables involved in the process. Compared with tableting, for example, in which small- and large-scale operations differ by speed only (the same die volume and same force can be assured), in wet granulation, one has to take into account the geometric, kinematic, and dynamic differences.

In this book, we recommend a universal approach to scale-up, a procedure called dimensional analysis. Dimensional analysis is widely used in many industries; in chemical engineering; and in applications such as fluid dynamics, heat and mass transfer, mixing of different substrates, homogenization, and so on (Zlokarnik, 2006). The method can be applied to any unit operation (in fact, any process) because any physical process can be described in terms of dimensionless variables. After this is achieved, the process becomes “scale invariable,” that is, independent of scale. In other words, the key to successful scale-up is to eliminate the scale (e.g., linear dimensions, time, forces) from the process description.

For wet granulation, the scientific approach to scale-up of an acceptable end point should include (1) understanding and application of the principles of dimensional analysis, (2) instrumentation to measure critical process parameters, (3) procedures to measure and calculate dimensional numbers describing your process, (4) creating a prediction equation that will calculate the required target dimensionless Newton power number Np, and (5) implementation of a computerized monitoring and control of your process that will stop the process when the desired Np is reached.

As a side note, we should mentions that improper scale-up of granulation process sometimes can only be detected on the tableting stage. If tablets made on the production press fail dissolution tests, the granule particle size or distribution can be the culprit.

Another note relates to Food and Drug Administration (FDA) Scale-Up and Post-Approval Changes (SUPAC) guidance (FDA Guidance: Scale-up and Post-Approval Changes for Modified Release Products [SUPAC-MR], 1995 and Scale-up and Post-Approval Changes Guidance for Immediate Release Products [SUPAC-IR], 1997). Postapproval scale-up changes are subject to regulatory oversight. If the process is different after scale-up, the manufacturer has to demonstrate that the product produced by a modified process will have similar bioavailability using data such as granulation studies, finished product test results, content uniformity, and potency and dissolution profiles. Although, generally speaking, postapproval scale-up or scale-down changes and recommendations covered by the FDA SUPAC guidance can be viewed from a dimensional analysis perspective, we will limit our discussions to scale-up principles and procedures during product and process development before regulatory approval. Postapproval changes just add another layer of complexity and risk to the whole process of scale-up.

Chapter 2

Dimensional Analysis

Abstract

This chapter introduces readers to the main concepts of the dimensional analysis technique used in many industries for scientific scale-up procedures. It discusses the principle of similitude in theory of modeling; dimensionless numbers such as Newton power number, Froude number, and Reynolds number; the Π-theorem of Buckingham; the Relevance List; and simple matrix transformations used to generate dimensionless numbers. Under the condition of total similarity of the process at different scales, these numbers should fully describe the state of the process, and their numerical value will be identical at every state and at every scale.

The dimensional analysis procedure is illustrated by examples for wet granulation, dry granulation, and tableting unit operations.

Keywords

dimensional analysis; relevance list; dimensional matrix; dimensionless numbers; scale-up

Outline

2.1 Theory of Modeling and Principle of Similitude

2.1.1 Geometrical Similarity

2.1.2 Kinematic Similarity

2.1.3 Dynamic Similarity

2.2 Dimensionless Numbers

2.3 Π-Theorem

2.4 Relevance List

2.5 Dimensional Matrix

2.6 Examples

2.6.1 Wet Granulation Example

2.6.2 Dry Granulation (Roller Compaction) Example

2.6.3 Compaction (Tableting) Example

2.7 Comparison of Attainable Froude Numbers

Dimensional analysis is based on the assumption that a mathem...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Acknowledgments
• About the Expertise in Pharmaceutical Process Technology Series
• Introduction
• Chapter 1. Scale-Up Basics
• Chapter 2. Dimensional Analysis
• Chapter 3. Wet Granulation
• Chapter 4. Recommended Procedures: Case Studies
• Chapter 5. Practical Considerations for End-Point Scale-Up
• Chapter 6. List of Symbols and Dimensions
• References
• Index