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Liu Z, Ma H, Zhou L, Liu Y, Huang Z, Liao X, Zhao Y. DEM-DDM Investigation of the Tablet Coating Process Using Different Particle Shape Models. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c04030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Zihan Liu
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Huaqing Ma
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Lianyong Zhou
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Yanlei Liu
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Ze Huang
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Xiaoling Liao
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Yongzhi Zhao
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
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2
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Modeling of inter-tablet coating uniformity of electrostatic dry powder coating by discrete element method. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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3
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Forgber T, Rehrl J, Matic M, Sibanc R, Sivanesapillai R, Khinast J. Experimental and numerical investigations of the RTD in a GEA ConsiGma CTL25 tablet press. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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4
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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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5
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A hybrid workflow for investigating wide DEM parameter spaces. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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6
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Wolfgang M, Stranzinger S, Khinast JG. Ascertain a minimum coating thickness for acid protection of enteric coatings by means of optical coherence tomography. Int J Pharm 2022; 618:121680. [PMID: 35314279 DOI: 10.1016/j.ijpharm.2022.121680] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 11/18/2022]
Abstract
Enteric coatings are designed to protect active pharmaceutical ingredients (APIs) against untimely release in the stomach. Acid protection of such coatings depends on the coating layer thickness and integrity, which must be determined in an accurate and reliable way to ensure the final product's desired performance. Our work addresses the use of optical coherence tomography (OCT) for characterizing the coating thickness and variability of an enteric-coated drug product and linking them to resistance against gastric fluid. In this study, three batches of enteric-coated tablets drawn during the manufacturing process were investigated. An industrial OCT system was used to establish the coating thickness variability of single tablets (intra-tablet), all tablets in a batch (inter-tablet) and between the batches (inter-batch). Based on the large amount of OCT data, we calculated a critical coating thickness for the investigated film coating, which was found to be 27.4 µm. The corresponding distribution has a mean coating thickness of 44.3 µm ± 7.8 µm. The final coated product has a final mean coating thickness of 63.4 µm ± 8.7 µm, guaranteeing that all tablets meet the quality criterion (i.e., acid protection). Based on the measured thickness distributions, already known distribution functions were considered and an additional, new function was proposed for characterizing the coating thickness distributions in the early stages of industrial coating processes. The proposed approach can be transferred to in-line monitoring of the tablet coating processes, which could drastically improve the production efficiency by ultimately allowing real-time release testing (RTRT).
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Affiliation(s)
- Matthias Wolfgang
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria
| | - Sandra Stranzinger
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria
| | - Johannes G Khinast
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria; Institute for Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria.
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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 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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8
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9
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Sacher S, Poms J, Rehrl J, Khinast JG. PAT implementation for advanced process control in solid dosage manufacturing - A practical guide. Int J Pharm 2021; 613:121408. [PMID: 34952147 DOI: 10.1016/j.ijpharm.2021.121408] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/10/2021] [Accepted: 12/16/2021] [Indexed: 01/14/2023]
Abstract
The implementation of continuous pharmaceutical manufacturing requires advanced control strategies rather than traditional end product testing or an operation within a small range of controlled parameters. A high level of automation based on process models and hierarchical control concepts is desired. The relevant tools that have been developed and successfully tested in academic and industrial environments in recent years are now ready for utilization on the commercial scale. To date, the focus in Process Analytical Technology (PAT) has mainly been on achieving process understanding and quality control with the ultimate goal of real-time release testing (RTRT). This work describes the workflow for the development of an in-line monitoring strategy to support PAT-based real-time control actions and its integration into solid dosage manufacturing. All stages are discussed in this paper, from process analysis and definition of the monitoring task to technology assessment and selection, its process integration and the development of data acquisition.
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Affiliation(s)
- Stephan Sacher
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria.
| | - Johannes Poms
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria
| | - Jakob Rehrl
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria
| | - Johannes G Khinast
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010 Graz, Austria; Institute for Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13/3, 8010 Graz, Austria
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10
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Comparative study of discrete element modeling of tablets using multi-spheres, multi-super-ellipsoids, and polyhedrons. POWDER TECHNOL 2021. [DOI: 10.1016/j.powtec.2021.05.065] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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11
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Siegmann E, Enzinger S, Toson P, Doshi P, Khinast J, Jajcevic D. Massively speeding up DEM simulations of continuous processes using a DEM extrapolation. POWDER TECHNOL 2021. [DOI: 10.1016/j.powtec.2021.05.067] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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12
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Cabiscol R, Finke JH, Kwade A. A bi-directional DEM-PBM coupling to evaluate chipping and abrasion of pharmaceutical tablets. ADV POWDER TECHNOL 2021. [DOI: 10.1016/j.apt.2021.06.002] [Citation(s) in RCA: 1] [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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13
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Xie C, Ma H, Song T, Zhao Y. DEM investigation of SAG mill with spherical grinding media and non-spherical ore based on polyhedron-sphere contact model. POWDER TECHNOL 2021. [DOI: 10.1016/j.powtec.2021.03.042] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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14
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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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15
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Lu L, Gao X, Shahnam M, Rogers WA. Open source implementation of glued sphere discrete element method and nonspherical biomass fast pyrolysis simulation. AIChE J 2021. [DOI: 10.1002/aic.17211] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Liqiang Lu
- National Energy Technology Laboratory Morgantown West Virginia USA
- Leidos Research Support Team Morgantown West Virginia USA
| | - Xi Gao
- National Energy Technology Laboratory Morgantown West Virginia USA
- Leidos Research Support Team Morgantown West Virginia USA
| | - Mehrdad Shahnam
- National Energy Technology Laboratory Morgantown West Virginia USA
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16
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Shi G, Lin L, Liu Y, Chen G, Luo Y, Wu Y, Li H. Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets. RSC Adv 2021; 11:8323-8345. [PMID: 35423324 PMCID: PMC8695199 DOI: 10.1039/d0ra08030f] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 01/26/2021] [Indexed: 11/21/2022] Open
Abstract
The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.
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Affiliation(s)
- Guolin Shi
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Longfei Lin
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuling Liu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Gongsen Chen
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuting Luo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yanqiu Wu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Hui Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
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17
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Xie C, You Y, Ma H, Zhao Y. Mechanism of inter-tablet coating variability: Investigation about the motion behavior of ellipsoidal tablets in a pan coater. POWDER TECHNOL 2021. [DOI: 10.1016/j.powtec.2020.10.088] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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18
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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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19
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Hirschberg C, Edinger M, Holmfred E, Rantanen J, Boetker J. Image-Based Artificial Intelligence Methods for Product Control of Tablet Coating Quality. Pharmaceutics 2020; 12:pharmaceutics12090877. [PMID: 32942536 PMCID: PMC7558946 DOI: 10.3390/pharmaceutics12090877] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 09/08/2020] [Accepted: 09/11/2020] [Indexed: 11/16/2022] Open
Abstract
Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets.
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Affiliation(s)
| | - Magnus Edinger
- Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark; (M.E.); (J.R.)
| | - Else Holmfred
- Research Group for Nano-Bio Science, National Food Institute, Technical University of Denmark, Kemitorvet, 2800 Kgs. Lyngby, Denmark;
| | - Jukka Rantanen
- Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark; (M.E.); (J.R.)
| | - Johan Boetker
- Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark; (M.E.); (J.R.)
- Correspondence:
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20
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Seo KS, Bajracharya R, Lee SH, Han HK. Pharmaceutical Application of Tablet Film Coating. Pharmaceutics 2020; 12:pharmaceutics12090853. [PMID: 32911720 PMCID: PMC7558083 DOI: 10.3390/pharmaceutics12090853] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 08/27/2020] [Accepted: 09/03/2020] [Indexed: 12/27/2022] Open
Abstract
Tablet film coating is a common but critical process providing various functionalities to tablets, thereby meeting diverse clinical needs and increasing the value of oral solid dosage forms. Tablet film coating is a technology-driven process and the evolution of coated dosage forms relies on advancements in coating technology, equipment, analytical techniques, and coating materials. Although multiple coating techniques are developed for solvent-based or solvent-free coating processes, each method has advantages and disadvantages that may require continuous technical refinement. In the film coating process, intra- and inter-batch coating uniformity of tablets is critical to ensure the quality of the final product, especially for active film coating containing active pharmaceutical ingredients in the coating layer. In addition to experimental evaluation, computational modeling is also actively pursued to predict the influence of operation parameters on the quality of the final product and optimize process variables of tablet film coating. The concerted efforts of experiments and computational modeling can save time and cost in optimizing the tablet coating process. This review provides a brief overview of tablet film coating technology and modeling approaches with a focus on recent advancements in pharmaceutical applications.
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Affiliation(s)
- Ki-Soo Seo
- College of Pharmacy, Dongguk University-Seoul, Dongguk-ro-32, Ilsan-Donggu, Goyang 10326, Korea; (K.-S.S.); (R.B.); (S.H.L.)
- Research Institute, Dong Wha Pharm., Tapsil-ro-35, Giheung-gu, Yongin 17084, Korea
| | - Rajiv Bajracharya
- College of Pharmacy, Dongguk University-Seoul, Dongguk-ro-32, Ilsan-Donggu, Goyang 10326, Korea; (K.-S.S.); (R.B.); (S.H.L.)
| | - Sang Hoon Lee
- College of Pharmacy, Dongguk University-Seoul, Dongguk-ro-32, Ilsan-Donggu, Goyang 10326, Korea; (K.-S.S.); (R.B.); (S.H.L.)
| | - Hyo-Kyung Han
- College of Pharmacy, Dongguk University-Seoul, Dongguk-ro-32, Ilsan-Donggu, Goyang 10326, Korea; (K.-S.S.); (R.B.); (S.H.L.)
- Correspondence: ; Tel.: +82-31-961-5217; Fax: +82-31-961-5206
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21
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Matić J, Paudel A, Bauer H, Garcia RAL, Biedrzycka K, Khinast JG. Developing HME-Based Drug Products Using Emerging Science: a Fast-Track Roadmap from Concept to Clinical Batch. AAPS PharmSciTech 2020; 21:176. [PMID: 32572701 PMCID: PMC7308264 DOI: 10.1208/s12249-020-01713-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 05/13/2020] [Indexed: 12/11/2022] Open
Abstract
This paper presents a rational workflow for developing enabling formulations, such as amorphous solid dispersions, via hot-melt extrusion in less than a year. First, our approach to an integrated product and process development framework is described, including state-of-the-art theoretical concepts, modeling, and experimental characterization described in the literature and developed by us. Next, lab-scale extruder setups are designed (processing conditions and screw design) based on a rational, model-based framework that takes into account the thermal load required, the mixing capabilities, and the thermo-mechanical degradation. The predicted optimal process setup can be validated quickly in the pilot plant. Lastly, a transfer of the process to any GMP-certified manufacturing site can be performed in silico for any extruder based on our validated computational framework. In summary, the proposed workflow massively reduces the risk in product and process development and shortens the drug-to-market time for enabling formulations.
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Affiliation(s)
- Josip Matić
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria
| | - Amrit Paudel
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria.
- Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria.
| | - Hannes Bauer
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria
| | | | | | - Johannes G Khinast
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria.
- Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria.
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22
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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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23
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Determining key parameters of continuous wet granulation for tablet quality and productivity: A case in ethenzamide. Int J Pharm 2020; 579:119160. [PMID: 32081803 DOI: 10.1016/j.ijpharm.2020.119160] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 01/29/2020] [Accepted: 02/16/2020] [Indexed: 11/24/2022]
Abstract
This paper aims to determine key parameters that affect tablet quality and productivity in continuous tablet manufacturing. Experiments were performed based on design of experiments using a continuous high-shear granulator and ethenzamide as the active pharmaceutical ingredient. To guide a systematic and comprehensive parameter analysis, a parameter framework was defined that comprised five input parameters on raw material properties and process parameters, 11 intermediate parameters on granule properties, and 11 output parameters on tablet quality and productivity. The interrelationships were analyzed statistically and were described as matrix functions. The liquid/solid ratio was the key parameter that affected circularity, density, and flowability as the granule properties, and disintegration and dissolution as the tablet quality. The maximum acceptable manufacturing rate that governs productivity was also affected by the liquid/solid ratio. Circularity was found to affect disintegration and dissolution. This result was specific to the setup of the study, but suggested development opportunities for a new process analytical technology system/quality-by-design application based on circularity. In addition, practical findings were obtained as follows: (1) high-speed manufacturing favored a lower liquid/solid ratio, and (2) high circularity slowed down disintegration/dissolution. This obtained knowledge will enhance the applicability of continuous technology in an actual manufacturing environment.
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Forgber T, Toson P, Madlmeir S, Kureck H, Khinast JG, Jajcevic D. Extended validation and verification of XPS/AVL-Fire™, a computational CFD-DEM software platform. POWDER TECHNOL 2020. [DOI: 10.1016/j.powtec.2019.11.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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25
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How to measure coating thickness of tablets: Method comparison of optical coherence tomography, near-infrared spectroscopy and weight-, height- and diameter gain. Eur J Pharm Biopharm 2019; 142:344-352. [DOI: 10.1016/j.ejpb.2019.06.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 05/24/2019] [Accepted: 06/18/2019] [Indexed: 11/18/2022]
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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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Madlmeir S, Loidolt P, Khinast JG. Study of the capsule-filling dosator process via calibrated DEM simulations. Int J Pharm 2019; 567:118441. [PMID: 31212054 DOI: 10.1016/j.ijpharm.2019.06.032] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 06/12/2019] [Accepted: 06/14/2019] [Indexed: 10/26/2022]
Abstract
Capsule filling is frequently accomplished via the dosator process. Controlling the main quality attributes, i.e., the fill weight and the fill weight variability, requires excellent process understanding. For the investigation of critical process parameters of low-dose capsule filling, DEM simulations were used. Two contact models (Hertz model and Luding model) were calibrated and validated to represent the lactose powder Lactohale 100. Both models gave good results, yet the Luding model resulted in better predictions. Since the dosator process is a volume-based approach, the dosator geometry is an important factor. We provide evidence that not only the volume, but also the proportions of the dosator affect the capsule fill weight. Slim nozzle chambers cause lower mass due to increased wall friction impact. The process is not volumetric, as a fill weight to volume correlation does not exist. Furthermore, the fill weight increases with higher powder beds and smaller gaps between the nozzle tip and the container bottom due to higher densification of the powder. Fill weight variations due to bed inhomogeneity were investigated by varying the bulk density of the initial powder bed.
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Affiliation(s)
- Stefan Madlmeir
- Institute of Process and Particle Engineering, TU Graz, Inffeldgasse 13, 8010 Graz, Austria; Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria
| | - Peter Loidolt
- Institute of Process and Particle Engineering, TU Graz, Inffeldgasse 13, 8010 Graz, Austria
| | - Johannes G Khinast
- Institute of Process and Particle Engineering, TU Graz, Inffeldgasse 13, 8010 Graz, Austria; Research Center Pharmaceutical Engineering, Inffeldgasse 13, 8010 Graz, Austria.
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Kureck H, Govender N, Siegmann E, Boehling P, Radeke C, Khinast JG. Industrial scale simulations of tablet coating using GPU based DEM: A validation study. Chem Eng Sci 2019. [DOI: 10.1016/j.ces.2019.03.029] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Sacher S, Wahl P, Weißensteiner M, Wolfgang M, Pokhilchuk Y, Looser B, Thies J, Raffa A, Khinast JG. Shedding light on coatings: Real-time monitoring of coating quality at industrial scale. Int J Pharm 2019; 566:57-66. [DOI: 10.1016/j.ijpharm.2019.05.048] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 05/17/2019] [Accepted: 05/17/2019] [Indexed: 10/26/2022]
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In silico predictions of tablet density using a quantitative structure–property relationship model. Int J Pharm 2019; 558:351-356. [DOI: 10.1016/j.ijpharm.2018.12.087] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 12/12/2018] [Accepted: 12/29/2018] [Indexed: 11/15/2022]
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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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Matsunami K, Miyano T, Arai H, Nakagawa H, Hirao M, Sugiyama H. Decision Support Method for the Choice between Batch and Continuous Technologies in Solid Drug Product Manufacturing. Ind Eng Chem Res 2018. [DOI: 10.1021/acs.iecr.7b05230] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Kensaku Matsunami
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Takuya Miyano
- Formulation Technology Research Laboratories, Pharmaceutical Technology Division, Daiichi Sankyo Co., Ltd., 1-12-1, Shinomiya, Hiratsuka, Kanagawa 254-0014, Japan
| | - Hiroaki Arai
- Formulation Technology Research Laboratories, Pharmaceutical Technology Division, Daiichi Sankyo Co., Ltd., 1-12-1, Shinomiya, Hiratsuka, Kanagawa 254-0014, Japan
| | - Hiroshi Nakagawa
- Formulation Technology Research Laboratories, Pharmaceutical Technology Division, Daiichi Sankyo Co., Ltd., 1-12-1, Shinomiya, Hiratsuka, Kanagawa 254-0014, Japan
| | - Masahiko Hirao
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Hirokazu Sugiyama
- Department of Chemical System Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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Ban J, Kumar R, Agarwal S, Wassgren C. Scaling inter‐tablet coating variability in a horizontal rotating drum. AIChE J 2017. [DOI: 10.1002/aic.15758] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- J. Ban
- School of Mechanical EngineeringPurdue UniversityWest Lafayette IN47907
| | - R. Kumar
- School of Mechanical EngineeringPurdue UniversityWest Lafayette IN47907
| | - S. Agarwal
- School of Mechanical EngineeringPurdue UniversityWest Lafayette IN47907
| | - C. Wassgren
- School of Mechanical EngineeringPurdue UniversityWest Lafayette IN47907
- Dept. of Industrial and Physical Pharmacy (by courtesy)Purdue UniversityWest Lafayette IN47907
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