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A Compact Model for Lyophilizer Equipment Capability Estimation.

Authors :
Kazarin P
Kessler W
Gong E
Yoon S
Liu H
Marx R
Bogner R
Alexeenko A
Source :
AAPS PharmSciTech [AAPS PharmSciTech] 2021 Dec 09; Vol. 23 (1), pp. 14. Date of Electronic Publication: 2021 Dec 09.
Publication Year :
2021

Abstract

This work presents a compact model for the equipment capability limit of a common configuration of pharmaceutical lyophilizers, a product chamber separated from the condenser by a duct and isolation valve, at a wide range of design parameters. The equipment capability limit is one of the most important characteristics determining the lyophilization design space for a particular product, container, and equipment combination. Experimental measurements of equipment capability are time-consuming and expensive, especially at the production scale. Numerical modeling using computational fluid dynamics may reduce the number of experiments and provide insights into the physics of the process with high resolution. The computational fluid dynamics (CFD) modeling has been used in this work to develop a compact model for lyophilizer equipment capability. This eliminates the need for end users to create a full CFD model of the equipment and process. Full CFD and compact model simulations for laboratory and pilot-scale lyophilizers have been compared with tunable diode laser absorption spectroscopy measurements of the water vapor mass flow during ice slab tests. The compact model results average deviation from the experimental data is within 10%, whereas the full CFD simulations are within 5%. The compact model is based on several key parameters which are the main characteristics of a lyophilizer affecting the equipment capability curve. These parameters are discussed, and their effect on the modeling results is shown.<br /> (© 2021. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Details

Language :
English
ISSN :
1530-9932
Volume :
23
Issue :
1
Database :
MEDLINE
Journal :
AAPS PharmSciTech
Publication Type :
Academic Journal
Accession number :
34888739
Full Text :
https://doi.org/10.1208/s12249-021-02167-8