Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data

Tanabe, Shigeru; Watanabe, Tetsu; Minami, Hidemi; Kano, Manabu; Urbanetz, Nora Anne

doi:10.1016/j.ijpharm.2016.07.023

Cited by 11 publications

(4 citation statements)

References 21 publications

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“…The atomization pressure, pan speed, and coating time were identified as CPPs affecting content uniformity. For the film coating process, Tanabe et al 133 generated a PLS model according to the data derived from the production process. Moreover, Cahyadi et al 134 used a multivariate model combined with DoE to optimize process parameters in the quasi-continuous tablet coating process.…”

Section: Application Of Multivariate Modeling Techniques In Tablet Ma...mentioning

confidence: 99%

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

et al. 2021

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Section: Application Of Multivariate Modeling Techniques In Tablet Ma...mentioning

confidence: 99%

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

et al. 2021

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“…In this study, three types of gray-box models, i.e., parallel, 16) serial, 17) and combined 18) gray-box models (see Fig. 1), were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) 19) model (black-box model). LW-PLSR was adopted as a regression method to address collinearity and nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation

2022

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Soft sensors are powerful tools for the implementation of process analytical technology (PAT). They are categorized into white-box (first-principle), black-box (statistical), and gray-box models. Gray-box models integrate white-box and black-box models to address each drawback, i.e., prediction accuracy and intuitiveness. Although they have been applied to various industrial processes, their applicability to water content monitoring in fluidized bed granulation has not been reported. In this study, we evaluated three types of gray-box models, i.e., parallel, serial, and combined gray-box models, in terms of prediction accuracy using real operating data on a commercial scale with two formulations. The gray-box models were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) model (black-box model). LW-PLSR was utilized to cope with collinearity and nonlinearity. In the serial gray-box models, LW-PLSR models adjusted the fitting parameters of the white-box model depending on the process parameters for each query. In the parallel gray-box or combined gray-box models, LW-PLSR models compensated for the output error of the white-box or serial gray-box models, respectively. The results demonstrated that all three types of gray-box models improved the prediction accuracy of the white-box models regardless of the formulation. Besides, we proposed the assessment method based on Hotelling's T 2 and Q residual for gray-box models using LW-PLSR, which contributes decision support to select gray-box or white-box model. The accurate and descriptive gray-box models are expected to enhance process understanding and precise quality control in fluidized bed granulation.

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“…Then, the laboratory equipment is typically scaled to the pilot scale with a drum load of 10-50 kg (14). Experiments on the industrial scale are carried out at the end of process development (15,16) using the intended commercial equipment and involving hundreds of kg of material. The product and technology transfer is accomplished based on existing empirical scale-up rules and experience of the operating engineers (14,17).…”

Section: Introductionmentioning

confidence: 99%

“…However, scale-up often causes problems due to changes in the coater geometry designs across the scales or completely different drum designs on the production vs. the pilot scale. Thus, the general goal is to reduce the number of experiments required on a large scale, since they are expensive due to time and material consumption (16).…”

Section: Introductionmentioning

confidence: 99%

Validating a Numerical Simulation of the ConsiGma(R) Coater

Boehling

Jacevic

Detobel³

et al. 2020

AAPS PharmSciTech

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Continuous manufacturing is increasingly used in the pharmaceutical industry, as it promises to deliver better product quality while simultaneously increasing production flexibility. GEA developed a semi-continuous tablet coater which can be integrated into a continuous tableting line, accelerating the switch from traditional batch production to the continuous mode of operation. The latter offers certain advantages over batch production, e.g., operational flexibility, increased process/product quality, and decreased cost. However, process understanding is the key element for process control. In this regard, computational tools can improve the fundamental understanding and process performance, especially those related to new processes, such as continuous tablet coating where process mechanics remain unclear. The discrete element method (DEM) and computational fluid dynamics (CFD) are two methods that allow transition from empirical process design to a mechanistic understanding of the individual process units. The developed coupling model allows to track the heat, mass, and momentum exchange between the tablet and fluid phase. The goal of this work was to develop and validate a high-fidelity CFD-DEM simulation model of the tablet coating process in the GEA ConsiGma® coater. After the model development, simulation results for the tablet movement, coating quality, and heat and mass transfer during the coating process were validated and compared to the experimental outcomes. The experimental and simulation results agreed well on all accounts measured, indicating that the model can be used in further studies to investigate the operating space of the continuous tablet coating process.

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Setting the process parameters for the coating process in order to assure tablet appearance based on multivariate analysis of prior data

Cited by 11 publications

References 21 publications

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation

Validating a Numerical Simulation of the ConsiGma(R) Coater

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