Modeling of Semicontinuous Fluid Bed Drying of Pharmaceutical Granules With Respect to Granule Size.


Journal

Journal of pharmaceutical sciences
ISSN: 1520-6017
Titre abrégé: J Pharm Sci
Pays: United States
ID NLM: 2985195R

Informations de publication

Date de publication:
06 2019
Historique:
received: 24 08 2018
revised: 06 12 2018
accepted: 11 01 2019
pubmed: 23 1 2019
medline: 18 7 2020
entrez: 23 1 2019
Statut: ppublish

Résumé

In the transition of the pharmaceutical industry from batchwise to continuous drug product manufacturing, the drying process has proven challenging to control and understand. In a semicontinuous fluid bed dryer, part of the ConsiGma™ wet granulation line, the aforementioned production methods converge. Previous research has shown that the evolution of moisture content of the material in this system shows strong variation in function of the granule size, making the accurate prediction of this pharmaceutical critical quality attribute a complex case. In this work, the evolution of moisture content of the material in the system is modeled by a bottom-up approach. A single granule drying kinetics model is used to predict the moisture content evolution of a batch of material of a heterogeneous particle size, where it is the first time that the single granule drying mechanism is validated for different granule sizes. The batch approach was validated when the continuous material inflow rate and filling time of the dryer cell are constant. The original single granule drying kinetics model has been extended to capture the granules' equilibrium moisture content. Finally, the influence of drying air temperature is captured well with a droplet energy balance for the granules.

Identifiants

pubmed: 30668940
pii: S0022-3549(19)30028-0
doi: 10.1016/j.xphs.2019.01.013
pii:
doi:

Substances chimiques

Powders 0
Tablets 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2094-2101

Informations de copyright

Copyright © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Auteurs

Michael Ghijs (M)

Department of Data Analysis and Mathematical Modelling, BIOMATH, Ghent University, Oost-Vlaanderen, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Oost-Vlaanderen, Belgium. Electronic address: Michael.Ghijs@UGent.be.

Elisabeth Schäfer (E)

Discovery, Product Development and Supply, Janssen, Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium.

Ashish Kumar (A)

Discovery, Product Development and Supply, Janssen, Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium.

Philippe Cappuyns (P)

Discovery, Product Development and Supply, Janssen, Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium.

Ivo Van Assche (I)

Discovery, Product Development and Supply, Janssen, Pharmaceutical Companies of Johnson & Johnson, Beerse, Belgium.

Fien De Leersnyder (F)

Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Oost-Vlaanderen, Belgium.

Vaĺerie Vanhoorne (V)

Laboratory of Pharmaceutical Technology, Department of Pharmaceutical Analysis, Ghent University, Oost-Vlaanderen, Belgium.

Thomas De Beer (T)

Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Oost-Vlaanderen, Belgium. Electronic address: Thomas.DeBeer@UGent.be.

Ingmar Nopens (I)

Department of Data Analysis and Mathematical Modelling, BIOMATH, Ghent University, Oost-Vlaanderen, Belgium. Electronic address: Ingmar.Nopens@UGent.be.

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