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A coarse-grained parcel method for heat and mass transfer simulations of spray coating processes. ADV POWDER TECHNOL 2022. [DOI: 10.1016/j.apt.2022.103590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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2
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Li S, Zhao P, Xu J, Zhang L, Wang J. CFD-DEM simulation of polydisperse gas-solid flow of Geldart A particles in bubbling micro-fluidized beds. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117551] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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3
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Madlmeir S, Forgber T, Trogrlic M, Jajcevic D, Kape A, Contreras L, Carmody A, Liu P, Davies C, Sarkar A, Khinast J. Quantifying the Coating Yield by Modeling Heat and Mass Transfer in a Wurster Fluidized Bed Coater. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117505] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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4
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Sansare S, Aziz H, Sen K, Patel S, Chaudhuri B. Computational Modeling of Fluidized Beds with a Focus on Pharmaceutical Applications: A Review. J Pharm Sci 2021; 111:1110-1125. [PMID: 34555391 DOI: 10.1016/j.xphs.2021.09.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 09/10/2021] [Accepted: 09/10/2021] [Indexed: 11/29/2022]
Abstract
The fluidized bed is an essential and standard equipment in the field of process development. It has a wide application in various areas and has been extensively studied. This review paper aims to discuss computational modeling of a fluidized bed with a focus on pharmaceutical applications. Eulerian, Lagrangian, and combined Eulerian-Lagrangian models have been studied for fluid bed applications with the rise of modeling capabilities. Such models assist in optimizing the process parameters and expedite the process development cycle. This paper discusses the background of modeling and then summarizes research papers relevant to pharmaceutical unit operations.
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Affiliation(s)
- Sameera Sansare
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Hossain Aziz
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, CT 06269, USA
| | - Koyel Sen
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Shivangi Patel
- Department of Physiology and Neurobiology, University of Connecticut, Storrs, CT 06269, USA
| | - Bodhisattwa Chaudhuri
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT 06269, USA; Institute of Material Sciences, University of Connecticut, Storrs, CT 06269, USA; Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA.
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6
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Optimization of Wurster fluid bed coating: Mathematical model validated against pharmaceutical production data. POWDER TECHNOL 2021. [DOI: 10.1016/j.powtec.2021.03.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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7
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Madlmeir S, Forgber T, Trogrlic M, Jajcevic D, Kape A, Contreras L, Carmody A, Liu P, Davies C, Sarkar A, Khinast JG. Modeling the coating layer thickness in a pharmaceutical coating process. Eur J Pharm Sci 2021; 161:105770. [PMID: 33610738 DOI: 10.1016/j.ejps.2021.105770] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/25/2021] [Accepted: 02/15/2021] [Indexed: 11/16/2022]
Abstract
Although mechanistic numerical simulations can offer great insights into a process, they are limited with respect to resolved process time. While statistical models provide long-term predictability, determining the underlying probability distributions is often challenging. In this work, detailed CFD-DEM simulations of a pharmaceutical Wurster coating process for microspheres are used to evaluate the input parameters for a novel Monte-Carlo simulation approach. The combined strengths of both modeling approaches make it possible to predict the coating mass and thickness distributions over the entire process time. It was observed that smaller beads receive a thicker coating layer since they pass the spray zone closer to the nozzle. Moreover, it was established that, in contrast to the airflow rate, the spray rate has a great impact on the inter-particle coating variability. A stochastic model was developed to investigate the relative contribution of coating layer variability and fill weight variability to the product non-uniformity in a capsule filling process of Multiple Unit Pellet Systems (MUPS).
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Affiliation(s)
- S Madlmeir
- Research Center Pharmaceutical Engineering, Graz, Austria
| | - T Forgber
- Research Center Pharmaceutical Engineering, Graz, Austria
| | - M Trogrlic
- Research Center Pharmaceutical Engineering, Graz, Austria
| | - D Jajcevic
- Research Center Pharmaceutical Engineering, Graz, Austria
| | - A Kape
- Glatt, Integrated Process Solution, Binzen, Germany
| | - L Contreras
- Worldwide Research, Development and Medical, Pfizer Inc., Sandwich, UK
| | - A Carmody
- Worldwide Research, Development and Medical, Pfizer Inc., Sandwich, UK
| | - P Liu
- Worldwide Research, Development and Medical, Pfizer Inc., Groton CT, USA
| | - C Davies
- Worldwide Research, Development and Medical, Pfizer Inc., Groton CT, USA
| | - A Sarkar
- Worldwide Research, Development and Medical, Pfizer Inc., Groton CT, USA
| | - J G Khinast
- Research Center Pharmaceutical Engineering, Graz, Austria; Institute of Process and Particle Engineering, Technical University of Graz, Austria.
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8
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Norouzi HR. Simulation of pellet coating in Wurster coaters. Int J Pharm 2020; 590:119931. [PMID: 33011246 DOI: 10.1016/j.ijpharm.2020.119931] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 09/20/2020] [Accepted: 09/26/2020] [Indexed: 10/23/2022]
Abstract
A combination of computational fluid dynamics (CFD), discrete element method (DEM), and discrete droplet method (DDM), i.e., a CFD-DEM-DDM model, was developed to simulate coating of pellets in a Wurster coater. The model equations were implemented in parallel using an approach that uses the computational resources of both CPU and GPU. Effects of the gas flow pattern, inlet gas temperature, partition gap, and spray characteristics were studied on the process. Decreasing the peripheral gas velocity, increasing the central jet velocity, and reducing the partition gap caused more uniform distributions of the circulation time and draft tube time, while the inlet gas temperature had negligible effect on them. Very high jet velocity caused a wider distribution of the circulation time. The dynamics of the spray and its interaction with pellets had significant effects on the coating mass distribution. Widening the spray angle while maintaining the droplet size constant caused the most uniform coating mass distribution and the highest deposition rate. Heat and mass transfer conditions as well as the deposition pattern changed the distributions of the solvent content and temperature of the pellets.
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Affiliation(s)
- Hamid Reza Norouzi
- Center of Engineering and Multiscale Modeling of Fluid Flow (CEMF), Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnique), PO Box: 15875-4413, Hafez 424, Tehran, Iran.
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9
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Boehling P, Jacevic D, Detobel F, Holman J, Wareham L, Metzger M, Khinast JG. Validating a Numerical Simulation of the ConsiGma(R) Coater. AAPS PharmSciTech 2020; 22:10. [PMID: 33244725 PMCID: PMC7691303 DOI: 10.1208/s12249-020-01841-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 10/07/2020] [Indexed: 11/30/2022] Open
Abstract
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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10
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Analysis of flexible ribbon particle residence time distribution in a fluidised bed riser using three-dimensional CFD-DEM simulation. POWDER TECHNOL 2020. [DOI: 10.1016/j.powtec.2020.05.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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11
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Kieckhefen P, Pietsch S, Dosta M, Heinrich S. Possibilities and Limits of Computational Fluid Dynamics-Discrete Element Method Simulations in Process Engineering: A Review of Recent Advancements and Future Trends. Annu Rev Chem Biomol Eng 2020; 11:397-422. [PMID: 32169000 DOI: 10.1146/annurev-chembioeng-110519-075414] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Fluid-solid systems play a major role in a wide variety of industries, from pharmaceutical and consumer goods to chemical plants and energy generation. Along with this variety of fields comes a diversity in apparatuses and applications, most prominently fluidized and spouted beds, granulators and mixers, pneumatic conveying, drying, agglomeration, coating, and combustion. The most promising approach for modeling the flow in these systems is the CFD-DEM method, coupling computational fluid dynamics (CFD) for the fluid phase and the discrete element method (DEM) for the particles. This article reviews the progress in modeling particle-fluid flows with the CFD-DEM method. A brief overview of the basic method as well as methodical extensions of it are given. Recent applications of this simulation approach to separation and classification units, fluidized beds for both particle formation and energy conversion, comminution units, filtration, and bioreactors are reviewed. Future trends are identified and discussed regarding their viability.
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Affiliation(s)
- Paul Kieckhefen
- Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany;
| | - Swantje Pietsch
- Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany;
| | - Maksym Dosta
- Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany;
| | - Stefan Heinrich
- Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany;
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12
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Alves-Lima D, Song J, Li X, Portieri A, Shen Y, Zeitler JA, Lin H. Review of Terahertz Pulsed Imaging for Pharmaceutical Film Coating Analysis. SENSORS 2020; 20:s20051441. [PMID: 32155785 PMCID: PMC7085697 DOI: 10.3390/s20051441] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 02/27/2020] [Accepted: 03/02/2020] [Indexed: 12/02/2022]
Abstract
Terahertz pulsed imaging (TPI) was introduced approximately fifteen years ago and has attracted a lot of interest in the pharmaceutical industry as a fast, non-destructive modality for quantifying film coatings on pharmaceutical dosage forms. In this topical review, we look back at the use of TPI for analysing pharmaceutical film coatings, highlighting the main contributions made and outlining the key challenges ahead.
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Affiliation(s)
- Décio Alves-Lima
- Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK; (D.A.-L.); (J.S.); (X.L.)
| | - Jun Song
- Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK; (D.A.-L.); (J.S.); (X.L.)
- Department of Information Science, Nanjing Forestry University, Nanjing 210037, Jiangsu, China
| | - Xiaoran Li
- Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK; (D.A.-L.); (J.S.); (X.L.)
| | - Alessia Portieri
- TeraView Ltd., 1, Enterprise Cambridge Research Park, Cambridge CB25 9PD, UK;
| | - Yaochun Shen
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK;
| | - J. Axel Zeitler
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK;
| | - Hungyen Lin
- Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK; (D.A.-L.); (J.S.); (X.L.)
- Correspondence:
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Li L, Kemp I, Palmer M. A DEM-based mechanistic model for scale-up of industrial tablet coating processes. POWDER TECHNOL 2020. [DOI: 10.1016/j.powtec.2020.01.087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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14
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Jiang Z, Rieck C, Bück A, Tsotsas E. Modeling of inter- and intra-particle coating uniformity in a Wurster fluidized bed by a coupled CFD-DEM-Monte Carlo approach. Chem Eng Sci 2020. [DOI: 10.1016/j.ces.2019.115289] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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15
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Yeom SB, Ha ES, Kim MS, Jeong SH, Hwang SJ, Choi DH. Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry. Pharmaceutics 2019; 11:E414. [PMID: 31443327 PMCID: PMC6723742 DOI: 10.3390/pharmaceutics11080414] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 08/10/2019] [Accepted: 08/12/2019] [Indexed: 12/15/2022] Open
Abstract
Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types-material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.
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Affiliation(s)
- Su Bin Yeom
- Department of Pharmaceutical Engineering, Inje University, Gyeongnam 621-749, Korea
| | - Eun-Sol Ha
- College of Pharmacy, Pusan National University, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan 46241, Korea
| | - Min-Soo Kim
- College of Pharmacy, Pusan National University, Busandaehak-ro 63 beon-gil, Geumjeong-gu, Busan 46241, Korea.
| | | | - Sung-Joo Hwang
- College of Pharmacy, Yonsei University, 85 Songdogwahak-ro, Yeonsu-gu, Incheon 21983, Korea
| | - Du Hyung Choi
- Department of Pharmaceutical Engineering, Inje University, Gyeongnam 621-749, Korea.
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Lin W, Guoli Q, Zhenjie L, Songsong Z, Hassan M, Xuemin L, Huilin L. Numerical simulation of flow behavior of topped gas-particles jet in a bubbling fluidized bed. POWDER TECHNOL 2019. [DOI: 10.1016/j.powtec.2019.02.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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17
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Zhang Y, Li Y, Gao Z, Li G, Zhao Y, Duan C, Dong L. Effects of drag force correlations on the mixing and segregation of polydisperse gas‐solid fluidized bed by CFD‐DEM simulation. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23421] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Yong Zhang
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Yanjiao Li
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Zhonglin Gao
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Guofeng Li
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Yuemin Zhao
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Chenlong Duan
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
- School of Chemical Engineering and TechnologyChina University of Mining & TechnologyXuzhou 221116China
| | - Liang Dong
- Key Laboratory of Coal Processing and Efficient Utilization of Ministry of EducationChina University of Mining & TechnologyXuzhou 221116China
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19
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Particle scale modelling of mixing of ellipsoids and spheres in gas-fluidized beds by a modified drag correlation. POWDER TECHNOL 2019. [DOI: 10.1016/j.powtec.2018.11.054] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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20
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Böhling P, Khinast JG, Jajcevic D, Davies C, Carmody A, Doshi P, Am Ende MT, Sarkar A. Computational Fluid Dynamics-Discrete Element Method Modeling of an Industrial-Scale Wurster Coater. J Pharm Sci 2019; 108:538-550. [DOI: 10.1016/j.xphs.2018.10.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 10/04/2018] [Accepted: 10/05/2018] [Indexed: 11/26/2022]
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A Review of the Applications of OCT for Analysing Pharmaceutical Film Coatings. APPLIED SCIENCES-BASEL 2018. [DOI: 10.3390/app8122700] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Optical coherence tomography (OCT) has recently attracted a lot of interest in the pharmaceutical manufacturing industry as a fast, contactless and non-destructive modality for quantifying thin film coatings on pharmaceutical dosage forms, which cannot be resolved easily with other techniques. In this topical review, we present an overview of the research that has been performed to date, highlighting key differences between systems and outlining major challenges ahead.
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22
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23
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Zou Z, Zhao Y, Zhao H, Zhang L, Xie Z, Li H, Zhu Q. CFD simulation of solids residence time distribution in a multi-compartment fluidized bed. Chin J Chem Eng 2017. [DOI: 10.1016/j.cjche.2017.02.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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24
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Kannan AS, Jareteg K, Lassen NCK, Carstensen JM, Hansen MAE, Dam F, Sasic S. Design and performance optimization of gravity tables using a combined CFD-DEM framework. POWDER TECHNOL 2017. [DOI: 10.1016/j.powtec.2017.05.046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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25
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Börner M, Bück A, Tsotsas E. DEM-CFD investigation of particle residence time distribution in top-spray fluidised bed granulation. Chem Eng Sci 2017. [DOI: 10.1016/j.ces.2016.12.020] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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26
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Mixing quality in mono- and bidisperse systems under the influence of particle shape: A numerical and experimental study. POWDER TECHNOL 2017. [DOI: 10.1016/j.powtec.2016.11.072] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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27
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Gu C, Li P, Yuan Z, Yan Y, Luo D, Li B, Lu D. A new corrected formula to predict mean residence time of flexible filamentous particles in rotary dryers. POWDER TECHNOL 2016. [DOI: 10.1016/j.powtec.2016.08.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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28
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Kannan AS, Lassen NCK, Carstensen JM, Lund J, Sasic S. Segregation phenomena in gravity separators: A combined numerical and experimental study. POWDER TECHNOL 2016. [DOI: 10.1016/j.powtec.2016.07.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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29
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Wang H, Qiu G, Ye J, Yang W. Experimental study and modelling on gas–solid flow in a lab-scale fluidised bed with Wurster tube. POWDER TECHNOL 2016. [DOI: 10.1016/j.powtec.2016.01.025] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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