A computational model for finite element analysis of the freeze-drying process

Mascarenhas, W.J.; Akay, H. U.; Pikal, Michael J.

doi:10.1016/s0045-7825(96)00078-3

Cited by 111 publications

(79 citation statements)

References 15 publications

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“…The loss of ice as a function of time predicted by our model, is similar to the one obtained by Mascarenhas [6] with a finite element analysis of freeze-drying. Moreover, further experiments showed a good agreement with the model.…”

Section: Phenomenological Modelsupporting

confidence: 85%

A Study of Vacuum Freeze-Drying of Frozen Wet Papers

2001

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Vacuum freeze-drying of frozen wet papers was investigated experimentally. A freeze-drying facility was built to study the process by monitoring the various physical parameters (pressure, sample temperature, heater temperature, water content of the sample and cold panel temperature). A simple phenomenological model was developed to explain experimental results. The values of the physical parameters were optimized to make the process cost effective.

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Section: Phenomenological Modelsupporting

confidence: 85%

A Study of Vacuum Freeze-Drying of Frozen Wet Papers

2001

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“…Details of the model equations and assumptions are described elsewhere (9,13). The model describes the heat and mass transfer equations in frozen and dried regions of a single vial.…”

Section: Methodsmentioning

confidence: 99%

Investigation of Design Space for Freeze-Drying: Use of Modeling for Primary Drying Segment of a Freeze-Drying Cycle

et al. 2011

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Abstract. In this work, we explore the idea of using mathematical models to build design space for the primary drying portion of freeze-drying process. We start by defining design space for freeze-drying, followed by defining critical quality attributes and critical process parameters. Then using mathematical model, we build an insilico design space. Input parameters to the model (heat transfer coefficient and mass transfer resistance) were obtained from separate experimental runs. Two lyophilization runs are conducted to verify the model predictions. This confirmation of the model predictions with experimental results added to the confidence in the insilico design space. This simple step-by-step approach allowed us to minimize the number of experimental runs (preliminary runs to calculate heat transfer coefficient and mass transfer resistance plus two additional experimental runs to verify model predictions) required to define the design space. The established design space can then be used to understand the influence of critical process parameters on the critical quality attributes for all future cycles.

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“…Then Technalysis (Indianapolis, IN, USA) developed a finite element method based GUI software based on the algorithm described by Pikal. Details such as governing equations, boundary conditions, assumptions, and validations are described elsewhere [15,20]. In summary, the software uses an arbitrary LagrangianEulerian method to accurately model the sublimation front of the freeze-drying process in two-dimensional axisymmetric space.…”

Section: Finite Element Method-based Model Descriptionmentioning

confidence: 99%

“…It is capable of calculating product temperature at different interface locations by predicting the position and geometric shape of the moving interface. It is assumed that the interface thickness is infinitesimal; a binary mixture of water vapor and inert gas flows through the dried layer; the concentration of water vapor is in equilibrium with the ice at the interface; the moisture movement is slow in the porous region; the frozen region is considered to have uniform mass and heat transfer properties [20]. The assumptions are emphasized here again in order to clearly state the problem statement.…”

Section: Finite Element Method-based Model Descriptionmentioning

confidence: 99%

Finite Element Method (FEM) Modeling of Freeze-drying: Monitoring Pharmaceutical Product Robustness During Lyophilization

et al. 2015

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Abstract. Lyophilization is an approach commonly undertaken to formulate drugs that are unstable to be commercialized as ready to use (RTU) solutions. One of the important aspects of commercializing a lyophilized product is to transfer the process parameters that are developed in lab scale lyophilizer to commercial scale without a loss in product quality. This process is often accomplished by costly engineering runs or through an iterative process at the commercial scale. Here, we are highlighting a combination of computational and experimental approach to predict commercial process parameters for the primary drying phase of lyophilization. Heat and mass transfer coefficients are determined experimentally either by manometric temperature measurement (MTM) or sublimation tests and used as inputs for the finite element model (FEM)-based software called PASSAGE, which computes various primary drying parameters such as primary drying time and product temperature. The heat and mass transfer coefficients will vary at different lyophilization scales; hence, we present an approach to use appropriate factors while scaling-up from lab scale to commercial scale. As a result, one can predict commercial scale primary drying time based on these parameters. Additionally, the model-based approach presented in this study provides a process to monitor pharmaceutical product robustness and accidental process deviations during Lyophilization to support commercial supply chain continuity. The approach presented here provides a robust lyophilization scale-up strategy; and because of the simple and minimalistic approach, it will also be less capital intensive path with minimal use of expensive drug substance/active material.

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A computational model for finite element analysis of the freeze-drying process

Cited by 111 publications

References 15 publications

A Study of Vacuum Freeze-Drying of Frozen Wet Papers

A Study of Vacuum Freeze-Drying of Frozen Wet Papers

Investigation of Design Space for Freeze-Drying: Use of Modeling for Primary Drying Segment of a Freeze-Drying Cycle

Finite Element Method (FEM) Modeling of Freeze-drying: Monitoring Pharmaceutical Product Robustness During Lyophilization

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