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Vandeputte T, Ghijs M, De Beer T, Nopens I. Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying. Int J Pharm 2024; 657:124135. [PMID: 38643808 DOI: 10.1016/j.ijpharm.2024.124135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/28/2024] [Accepted: 04/16/2024] [Indexed: 04/23/2024]
Abstract
Pharmaceutical twin-screw wet granulation is a multifaceted and intricate process pivotal to drug product development. Accurate modeling of this process is indispensable for optimizing manufacturing parameters and ensuring product quality. The fluid bed dryer, an integral component of this granulation process, significantly influences the granular critical quality attributes. This study builds upon prior research by integrating experimental findings on granule segregation during fluid bed drying into an existing compartmental model, enhancing its predictive capabilities. An additional model layer on granule segregation behavior is composed and integrated into the existing model structure in this study. The added model compartment describes probability distributions on the vertical position of granules within each granule size class considered. To beware of overfitting, predictions of both the moisture content after drying and the granule bed temperature throughout drying are discussed in this study relative to experimental data from earlier published studies. These independent analyses demonstrated a marked improvement in prediction accuracy compared to earlier published model structures. The refined model accurately predicts the residual moisture content after drying for an untrained formulation. Moreover, it simultaneously makes accurate predictions of the granular bed temperature, which emboldens its structural correctness. This advancement makes it a powerful tool for predicting the behavior of the pharmaceutical fluid bed drying, which holds significant promise to facilitate pharmaceutical product development.
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Affiliation(s)
- Tuur Vandeputte
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium.
| | - Michael Ghijs
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium
| | - Thomas De Beer
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium.
| | - Ingmar Nopens
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium
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Vandeputte T, Ghijs M, Nopens I, De Beer T. A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying. AAPS PharmSciTech 2023; 25:11. [PMID: 38175363 DOI: 10.1208/s12249-023-02711-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 11/27/2023] [Indexed: 01/05/2024] Open
Abstract
Continuous twin screw wet granulation (TSWG) systems are possible pathways for oral solid dosage manufacturing in the pharmaceutical industry. TSWG requires a drying step after granulation before the tableting process. Typically, semi-continuous fluidized bed dryers (FBDs) are used for this purpose. At the same time, the pharmaceutical sector is interested in mathematical prediction models to save resources during the early drug product development (DPD) stage or to control manufacturing. Several authors have already developed prediction models for semi-continuous drying processes. However, these model structures reported systematic prediction offsets, which could be related to the incomplete implementation of fluidization and granule segregation phenomena. This study evaluates the complex fluidization behavior of wet granules in industrially relevant semi-continuous FBDs. A transparent perspex version of the dryer was used for the analysis of bed height, pressure drop, porosity, segregation, and spatial heating patterns at varying process settings. The investigated behaviors of the fluidizing bed will be helpful to derive phenomenological (sub)models for the detailed description of segregation in the semi-continuous fluidized bed system. In this study, it was found that semi-continuous FBDs are characterized by a change in fluidization regime from plug flow to a bubbling bed at the moment that the granule bed slumps. Secondly, the presence of size-based vertical segregation phenomena as well as spatial temperature differences were proven. The experimental results suggest that larger granules are dried under more intense drying conditions than smaller granules.
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Affiliation(s)
- Tuur Vandeputte
- Department of Data Analysis and Mathematical Modelling, BIOMATH, Ghent University, Oost-Vlaanderen, Belgium.
- Department of Pharmaceutical Analysis, Laboratory of Pharmaceutical Process Analytical Technology, Ghent University, Oost-Vlaanderen, Belgium.
| | - Michael Ghijs
- Department of Data Analysis and Mathematical Modelling, BIOMATH, Ghent University, Oost-Vlaanderen, Belgium
- Department of Pharmaceutical Analysis, Laboratory of Pharmaceutical Process Analytical Technology, Ghent University, Oost-Vlaanderen, Belgium
| | - Ingmar Nopens
- Department of Data Analysis and Mathematical Modelling, BIOMATH, Ghent University, Oost-Vlaanderen, Belgium
| | - Thomas De Beer
- Department of Pharmaceutical Analysis, Laboratory of Pharmaceutical Process Analytical Technology, Ghent University, Oost-Vlaanderen, Belgium
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Vandeputte T, Ghijs M, Van Hauwermeiren D, Dos Santos Schultz E, Schäfer E, Stauffer F, De Beer T, Nopens I. Mechanistic modeling of semicontinuous fluidized bed drying of pharmaceutical granules by incorporating single particle and bulk drying kinetics. Int J Pharm 2023; 646:123447. [PMID: 37770009 DOI: 10.1016/j.ijpharm.2023.123447] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/07/2023] [Accepted: 09/24/2023] [Indexed: 10/03/2023]
Abstract
In this work, a mechanistic fluidized bed drying model computing the granule moisture content in function of granule size, drying time, process settings and formulation properties is developed. Modeling the moisture content distribution concerning the granule size is essential for tabletability and drug product quality. This work combines a mechanistic bulk model and a single-particle drying kinetics model in a semicontinuous mode. The added model complexity allows physical approximations of drying phenomena at both the drying system level and the granular level. This includes quantifying the variations in moisture content by taking into account the specific dryer design and the variations in granule size. The model performance was quantified through industrially relevant case studies. It was revealed that the proposed model structure accurately predicts the drying behavior of the yield fraction. However, systematic model biases were observed for the fine and coarse fractions of the granule size distribution. In addition, discrepancies in the predicted outgoing air properties (relative air humidity and air temperature) were obtained. Further enhancement of the model complexity, e.g. complete incorporation of fluidization and segregation phenomena, is likely to improve the model performance. Notwithstanding, the developed model forms a step towards a formulation-generic fluidized bed drying model as interacting mechanisms on different levels of the drying system are considered.
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Affiliation(s)
- Tuur Vandeputte
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium
| | - Michael Ghijs
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium
| | - Daan Van Hauwermeiren
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium; Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium
| | | | - Elisabeth Schäfer
- Discovery, Product Development & Supply, Janssen R&D, B-2340 Beerse, Belgium
| | | | - Thomas De Beer
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, B-9000 Ghent, Belgium.
| | - Ingmar Nopens
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, B-9000 Ghent, Belgium
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Zhao J, Tian G, Qu H. Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation. Biomedicines 2023; 11:1923. [PMID: 37509561 PMCID: PMC10377609 DOI: 10.3390/biomedicines11071923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/15/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG.
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Affiliation(s)
- Jie Zhao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Geng Tian
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Haibin Qu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
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Casian T, Nagy B, Kovács B, Galata DL, Hirsch E, Farkas A. Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review. Molecules 2022; 27:4846. [PMID: 35956791 PMCID: PMC9369811 DOI: 10.3390/molecules27154846] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 12/03/2022] Open
Abstract
The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.
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Affiliation(s)
- Tibor Casian
- Department of Pharmaceutical Technology and Biopharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
| | - Brigitta Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Béla Kovács
- Department of Biochemistry and Environmental Chemistry, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș, 540139 Târgu Mureș, Romania;
| | - Dorián László Galata
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Edit Hirsch
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
| | - Attila Farkas
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Hungary; (D.L.G.); (E.H.); (A.F.)
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