Mechanistic modeling of high-shear and twin screw mixer granulation processes

A. Chaudhury, D. Barrasso, D. A. Pohlman, J. D. Litster, R. Ramachandran

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Particulate processes are ubiquitous in various industries, such as, pharmaceuticals, aerosols, and detergents, and are challenging to control owing to their discrete nature. Granulation is a particle design process used in the pharmaceutical industry to tailor the particle size and other attributes for improved handling. Granulation processes can be efficiently described using population balance models (PBMs) and discrete element modeling with efficient numerical techniques for accurate solution and the applicability of Quality by Design (QbD) in the process operation. The recent initiative by the US FDA suggesting the implementation of QbD in pharmaceutical processing has emphasized the need for a model-based system approach. In this chapter, a detailed discussion is provided on the applicability of modeling approaches for improved understanding of mixer wet granulation processes. The development of a semimechanistic model accentuates the ability to develop a predictive model for improved process operation. The implementation of efficient numerical techniques for solving PBMs is discussed in this chapter. A brief introduction is provided initially describing the underlying mechanisms and high-shear granulation equipment, and giving the readers an overview of QbD and its principles. The following sections focus on the mathematical models developed for describing granulation, the numerical techniques that can be applied for solving such models and more specific case studies that focus on problem solving using these techniques. Overall, this chapter aims to provide a comprehensive overview on the current state of high-shear granulation models with the implementation of a systems-based approach.

Original languageEnglish (US)
Title of host publicationPredictive Modeling of Pharmaceutical Unit Operations
PublisherElsevier Inc.
Pages99-135
Number of pages37
ISBN (Electronic)9780081001806
ISBN (Print)9780081001547
DOIs
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Medicine(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)

Keywords

  • Discrete element modeling
  • High-shear wet granulation
  • Population balance model
  • Process systems engineering
  • Quality by design

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