In-depth experimental analysis of pharmaceutical twin-screw wet granulation in view of detailed process understanding

Verstraeten, Maxim; Hauwermeiren, Daan Van; Lee, Kai; Turnbull, Neil; Wilsdon, David; Ende, M A; Doshi, Pankaj; Vervaet, Chris; Brouckaert, Davinia; Mortier, Séverine; Nopens, Ingmar; Beer, Thomas De

doi:10.1016/j.ijpharm.2017.07.045

Cited by 58 publications

(57 citation statements)

References 36 publications

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“…Wet granule size is influenced by all three granulator process variables. This finding conforms with experiments that show effect of these variables on granulation rate [12]. For the dryer model outputs, flow rate and granulator screw speed do not show influence on dry granule moisture content and all five input factors show influence on dry granule size and dry granule properties (bulk density, tapped density, and angle of repose).…”

Section: Sensitivity Analysis Resultssupporting

confidence: 89%

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Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route

et al. 2019

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In view of growing interest and investment in continuous manufacturing, the development and utilization of mathematical model(s) of the manufacturing line is of prime importance. These models are essential for understanding the complex interplay between process-wide critical process parameters (CPPs) and critical quality attributes (CQAs) beyond the individual process operations. In this work, a flowsheet model that is an approximate representation of the ConsiGma TM -25 line for continuous tablet manufacturing, including wet granulation, is developed. The manufacturing line involves various unit operations, i.e., feeders, blenders, a twin-screw wet granulator, a fluidized bed dryer, a mill, and a tablet press. The unit operations are simulated using various modeling approaches such as data-driven models, semi-empirical models, population balance models, and mechanistic models. Intermediate feeders, blenders, and transfer lines between the units are also simulated. The continuous process is simulated using the flowsheet model thus developed and case studies are provided to demonstrate its application for dynamic simulation. Finally, the flowsheet model is used to systematically identify critical process parameters (CPPs) that affect process responses of interest using global sensitivity analysis methods. Liquid feed rate to the granulator, and air temperature and drying time in the dryer are identified as CPPs affecting the tablet properties.

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Section: Sensitivity Analysis Resultssupporting

confidence: 89%

“…Specifically, the units involved are feeders, blenders, twin-screw wet granulator (TSWG), fluid bed dryer (FBD), comill, and tablet press. Models for these processes are developed [12][13][14][15][16] and included. Besides these, models for intermediate feeding and blending operations are also included.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route

et al. 2019

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“…One possible approach would be to aggregate the information contained in the whole distribution into a mean particle size, or an indication of the size of the largest or smallest particles. Typically, d 10 , d 50 , and d 90 are used to describe the particle size in experimental papers in this application field, as in the work of Verstraeten et al [2]. This approach is sensible if the underlying distribution is known.…”

Section: General Principlesmentioning

confidence: 99%

“…A more in-depth depiction of the TSWG can be found in Figure 7, displaying the input and output data of the system. The experimental set up of this paper is described in the work of Verstraeten et al [2]. Here, only a summary with the details relevant to this work is given.…”

Section: Experimental Set Up and Data Collectionmentioning

confidence: 99%

Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

2020

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In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma TM -25 continuous powder-to-tablet system (GEA Pharma systems, Collette, Wommelgem, Belgium), the product under study presents itself as a collection of particles that differ in shape and size. The measurement of this collection results in a particle size distribution. However, the theoretical basis to describe the physical phenomena leading to changes in this particle size distribution is lacking. It is essential to understand how the particle size distribution changes as a function of the unit operation's process settings, as it has a profound effect on the behavior of the fluid bed dryer. Therefore, we suggest a data-driven modeling framework that links the machine settings of the wet granulation unit operation and the output distribution of granules. We do this without making any assumptions on the nature of the distributions under study. A simulation of the granule size distribution could act as a soft sensor when in-line measurements are challenging to perform. The method of this work is a two-step procedure: first, the measured distributions are transformed into a high-dimensional feature space, where the relation between the machine settings and the distributions can be learnt. Second, the inverse transformation is performed, allowing an interpretation of the results in the original measurement space. Further, a comparison is made with previous work, which employs a more mechanistic framework for describing the granules. A reliable prediction of the granule size is vital in the assurance of quality in the production line, and is needed in the assessment of upstream (feeding) and downstream (drying, milling, and tableting) issues. Now that a validated data-driven framework for predicting pharmaceutical particle size distributions is available, it can be applied in settings such as model-based experimental design and, due to its fast computation, there is potential in real-time model predictive control.

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“…Due to the use of a liquid phase as binder, the ratio between the liquid and solid phases would affect the granule final properties [20]. If the liquid/solid ratio increases (due to a high amount of used liquid), nucleation is favored, but at the same time, it is possible that overwetting phenomena may occur, with consequent formation of a mixture and not granules.…”

Section: Formulation Parameters 2211 Effect Of Binder Addition Ratementioning

confidence: 99%

Inside the Phenomenological Aspects of Wet Granulation: Role of Process Parameters

Simone¹,

Caccavo²,

Dalmoro³

et al. 2018

Granularity in Materials Science

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Granulation is a size-enlargement process by which small particles are bonded, by means of various techniques, in coherent and stable masses (granules), in which the original particles are still identifiable. In wet granulation processes, the powder particles are aggregated through the use of a liquid phase called binder. The main purposes of sizeenlargement process of a powder or mixture of powders are to improve technological properties and/or to realize suitable forms of commercial products. A modern and rational approach in the production of granular structures with tailored features (in terms of size and size distribution, flowability, mechanical and release properties, etc.) requires a deep understanding of phenomena involved during granules formation. By this knowledge, suitable predictive tools can be developed with the aim to choose right process conditions to be used in developing new formulations by avoiding or reducing costs for new tests. In this chapter, after introductive notes on granulation process, the phenomenological aspects involved in the formation of the granules with respect to the main process parameters are presented by experimental demonstration. Possible mathematical approaches in the granulation process description are also presented and the one involving the population mass balances equations is detailed.

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In-depth experimental analysis of pharmaceutical twin-screw wet granulation in view of detailed process understanding

Cited by 58 publications

References 36 publications

Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route

Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route

Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

Inside the Phenomenological Aspects of Wet Granulation: Role of Process Parameters

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