High shear wet granulation modelling—a mechanistic approach using population balances

Darelius, Anders; Rasmuson, Anders; Björn, Ingela Niklasson; Folestad, Staffan

doi:10.1016/j.powtec.2005.08.036

Cited by 41 publications

(11 citation statements)

References 9 publications

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“…Kapur et al, 1969;Goldschmidt, 2001;Darelius et al, 2005). Goldschmidt (2001) has shown that, within the context of a two-fluid model, the number of collisions between particles of phases 1 and 2 per unit volume per unit time can be given by:…”

Section: Aggregation Ratementioning

confidence: 99%

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

Chua

Makkawi

Hounslow

2013

Chemical Engineering Science

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This paper presents a predictive aggregation rate model for spray fluidized bed melt granulation. The aggregation rate constant was derived from probability analysis of particle-droplet contact combined with time scale analysis of droplet solidification and granule-granule collision rates. The latter was obtained using the principles of Kinetic Theory of Granular Flow (KTGF). The predicted aggregation rate constants were validated by comparison with reported experimental data for a range of binder spray rate, binder droplet size and operating granulator temperature. The developed model is particularly useful for predicting particle size distributions and growth using population balance equations (PBE).

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Section: Aggregation Ratementioning

confidence: 99%

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

Chua

Makkawi

Hounslow

2013

Chemical Engineering Science

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“…The growth of particle size in the processes undergoing aggregation is typically modelled by a population balance method [3,24,[34][35][36][37][38][39][40][41][42][43][44][45][46][47][48] and for granular flow in such as gas fluidised bed (FB) systems, a kinetic theory approach [12,[49][50][51][52][53][54] can be adopted. For FB systems, the use of the kinetic theory to understand the motion of particles has become a common method [55][56][57][58] and experimental measurements [59][60][61][62][63][64] have validated the applicability of this method to some large extent.…”

Section: Introductionmentioning

confidence: 99%

Effects of aggregation on the kinetic properties of particles in fluidised bed granulation

Liu

2015

Powder Technology

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“…The mechanism of agglomeration has been wellstudied at the macroscopic and microscopic level. The former mainly describes an overall granulation process using power consumption, torque, and flow [1][2][3][4][5][6], while the latter investigates the coalescence and breakage mechanism on particle-particle levels from a fundamental viewpoint [7][8][9]. Several excellent review papers have been published [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…The population balance model [8,9] aims at representing the actual agglomeration processes based on first principles and may be another powerful approach for estimating the mechanical HSWG process parameters. If coalescence, breakage, and flow pattern are completely known, the kernel will be independent of the size of the bowl.…”

Section: Introductionmentioning

confidence: 99%

De-risking Scale-up of a High Shear Wet Granulation Process Using Latent Variable Modeling and Near-Infrared Spectroscopy

et al. 2011

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In the development of wet granulated drug products, two primary sources of variance (disturbance) include the operational scale of the high shear wet granulation (HSWG) process and active pharmaceutical ingredient (API) lot-to-lot variability, particularly for formulations containing a high drug load. This paper presents a novel Process Analytical Technology strategy using latent variable modeling with nearinfrared spectroscopy (NIRS) to reduce risk in scale-up operations of the HSWG process while simultaneously accounting for API lot-to-lot variability, even with limited manufacturing history. The process involves building a partial least square (PLS) model among the API material properties, the HSWG process parameters, and the NIRS end points of the HSWG process based on small-scale design of experiment batches. The PLS model is then used in an optimization framework to find suitable small-scale mechanical process parameters (impeller/chopper speed) that approximate a previous large-scale operation so as to keep the NIRS end point of large-scale operation constant. Prior to making additional large-scale batches with a new lot of API, NIRS end points of large-scale HSWG with the new API lot are predicted based on the PLS model developed from the smallscale operation. If the predicted NIRS end point for the HSWG using the new API lot is not within the target region, the risks associated with the scale-up operation can then be significantly reduced by modifying other HSWG process parameters such as the total amount of water added or total granulation time to achieve the target region. A case study is presented that demonstrates the effectiveness of this methodology during development and scale-up of a drug product manufactured using a HSWG process.

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High shear wet granulation modelling—a mechanistic approach using population balances

Cited by 41 publications

References 9 publications

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

Effects of aggregation on the kinetic properties of particles in fluidised bed granulation

De-risking Scale-up of a High Shear Wet Granulation Process Using Latent Variable Modeling and Near-Infrared Spectroscopy

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