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Jolliffe HG, Prostredny M, Mendez Torrecillas C, Bordos E, Tierney C, Ojo E, Elkes R, Reynolds G, Li Song Y, Meir B, Fathollahi S, Robertson J. A modified Kushner-Moore approach to characterising small-scale blender performance impact on tablet compaction. Int J Pharm 2024; 659:124232. [PMID: 38759740 DOI: 10.1016/j.ijpharm.2024.124232] [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: 01/30/2024] [Revised: 05/02/2024] [Accepted: 05/14/2024] [Indexed: 05/19/2024]
Abstract
Continuous Direct Compaction (CDC) has emerged as a promising route towards producing solid dosage forms while reducing material, development time and energy consumption. Understanding the response of powder processing unit operations, especially blenders, is crucial. There is a substantial body of work around how lubrication via batch blender operation affects tablet critical quality attributes such as hardness and tensile strength. But, aside from being batch operations, the design of these blenders is such that they operate with low-shear, low-intensity mixing at Froude number values significantly below 0.4 (Froude number Fr being the dimensionless ratio of inertial to gravitational forces). The present work explores the performance of a mini-blender which has a fundamentally different mode of operation (static vessel with rotating blades around a mixing shaft as opposed to rotating vessel with no mixing shaft). This difference allows a substantially wider operating range in terms of speed and shear (and Fr values). The present work evaluates how its performance compares to other blenders studied in the literature. Tablet compaction data from blends produced at various intensities and regimes of mixing in the mini-blender follow a common trajectory. Model equations from literature are suitably modified by inclusion of the Froude number Fr, but only for situations where the Froude number was sufficiently high (1 < Fr). The results suggest that although a similar lubrication extent plateau is eventually reached it is the intensity of mixing (i.e. captured using the Froude number as a surrogate) which is important for the lubrication dynamics in the mini-blender, next to the number of revolutions. The degree of fill or headspace, on the other hand, is only crucial to the performance of common batch blenders. Testing using alternative formulations shows the same common trend across mixing intensities, suggesting the validity of the approach to capture lubrication dynamics for this system.
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Affiliation(s)
- Hikaru G Jolliffe
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK
| | - Martin Prostredny
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK
| | | | - Ecaterina Bordos
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK
| | - Collette Tierney
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK
| | - Ebenezer Ojo
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK
| | - Richard Elkes
- GSK Ware R&D, Harris's Lane, Ware, Hertfordshire SG12 0GX, UK
| | - Gavin Reynolds
- Oral Product Development, PT&D, Operations, AstraZeneca UK Limited, Charter Way, Macclesfield SK10 2NA, UK
| | - Yunfei Li Song
- GSK Ware R&D, Harris's Lane, Ware, Hertfordshire SG12 0GX, UK
| | - Bernhard Meir
- Gericke AG, Althardstrasse 120, CH-8105 Regensdorf, Switzerland
| | - Sara Fathollahi
- DFE Pharma GmbH & Co. KG, Kleverstrasse 187, 47568 Goch, Germany
| | - John Robertson
- CMAC, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK.
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Matsunami K, Vandeputte T, Barrera Jiménez AA, Peeters M, Ghijs M, Van Hauwermeiren D, Stauffer F, Dos Santos Schultz E, Nopens I, De Beer T. Validation of model-based design of experiments for continuous wet granulation and drying. Int J Pharm 2023; 646:123493. [PMID: 37813175 DOI: 10.1016/j.ijpharm.2023.123493] [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: 07/07/2023] [Revised: 09/27/2023] [Accepted: 10/05/2023] [Indexed: 10/11/2023]
Abstract
This paper presents an application case of model-based design of experiments for the continuous twin-screw wet granulation and fluid-bed drying sequence. The proposed framework consists of three previously developed models. Here, we are testing the applicability of previously published unit operation models in this specific part of the production line to a new active pharmaceutical ingredient. Firstly, a T-shaped partial least squares regression model predicts d-values of granules after wet granulation with different process settings. Then, a high-resolution full granule size distribution is computed by a hybrid population balance and partial least squares regression model. Lastly, a mechanistic model of fluid-bed drying simulates drying time and energy efficiency, using the outputs of the first two models as a part of the inputs. In the application case, good operating conditions were calculated based on material and formulation properties as well as the developed process models. The framework was validated by comparing the simulation results with three experimental results. Overall, the proposed framework enables a process designer to find appropriate process settings with a less experimental workload. The framework combined with process knowledge reduced 73.2% of material consumption and 72.3% of time, especially in the early process development phase.
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Affiliation(s)
- Kensaku Matsunami
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium.
| | - Tuur Vandeputte
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Ana Alejandra Barrera Jiménez
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Michiel Peeters
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Michael Ghijs
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Daan Van Hauwermeiren
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Fanny Stauffer
- Product Design & Performance, UCB, Braine l'Alleud, 1420, Belgium
| | | | - Ingmar Nopens
- BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure links 653, Ghent, 9000, Oost-Vlaanderen, Belgium
| | - Thomas De Beer
- Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent, 9000, Oost-Vlaanderen, Belgium
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Zhu A, Mao C, Luner PE, Lomeo J, So C, Marchal S, Zhang S. Investigation of Quantitative X-ray Microscopy for Assessment of API and Excipient Microstructure Evolution in Solid Dosage Processing. AAPS PharmSciTech 2022; 23:117. [PMID: 35441297 DOI: 10.1208/s12249-022-02271-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 04/03/2022] [Indexed: 11/30/2022] Open
Abstract
Assessment and understanding of changes in particle size of active pharmaceutical ingredients (API) and excipients as a function of solid dosage form processing is an important but under-investigated area that can impact drug product quality. In this study, X-ray microscopy (XRM) was investigated as a method for determining the in situ particle size distribution of API agglomerates and an excipient at different processing stages in tablet manufacturing. An artificial intelligence (AI)-facilitated XRM image analysis tool was applied for quantitative analysis of thousands of individual particles, both of the API and the major filler component of the formulation, microcrystalline cellulose (MCC). Domain size distributions for API and MCC were generated along with the calculation of the porosity of each respective component. The API domain size distributions correlated with laser diffraction measurements and sieve analysis of the API, formulation blend, and granulation. The XRM analysis demonstrated that attrition of the API agglomerates occurred secondary to the granulation stage. These results were corroborated by particle size distribution and sieve potency data which showed generation of an API fines fraction. Additionally, changes in the XRM-calculated size distribution of MCC particles in subsequent processing steps were rationalized based on the known plastic deformation mechanism of MCC. The XRM data indicated that size distribution of the primary MCC particles, which make up the larger functional MCC agglomerates, is conserved across the stages of processing. The results indicate that XRM can be successfully applied as a direct, non-invasive method to track API and excipient particle properties and microstructure for in-process control samples and in the final solid dosage form. The XRM and AI image analysis methodology provides a data-rich way to interrogate the impact of processing stresses on API and excipients for enhanced process understanding and utilization for Quality by Design (QbD).
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Peddapatla RVG, Slevin C, Sheridan G, Beirne C, Swaminathan S, Browning I, O’Reilly C, Worku ZA, Egan D, Sheehan S, Crean AM. Modelling the Compaction Step of a Platform Direct Compression Process. Pharmaceutics 2022; 14:pharmaceutics14040695. [PMID: 35456529 PMCID: PMC9027228 DOI: 10.3390/pharmaceutics14040695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/06/2022] [Accepted: 03/16/2022] [Indexed: 02/01/2023] Open
Abstract
The ability to predict formulation behaviour at production scale during formulation design can reduce the time to market and decrease product development costs. However, it is challenging to extrapolate compaction settings for direct compression formulations between tablet press models during scale-up and transfer from R&D to commercial production. The aim of this study was to develop statistical process models to predict tablet tensile strength, porosity and disintegration time from compaction parameters (pre-compression and main compression force, and press speed), for three formulations, with differing deformation characteristics (plastic, brittle and elastic), on three tablet press models (one pilot-scale tablet press (KG RoTab) and two production-scale presses (Fette 1200i and GEA Modul P)). The deformation characteristics of yield pressure and elastic recovery were determined for the model placebo formulations investigated. To facilitate comparison of dwell time settings between tablet press models, the design of experiments (DoE) approach was 9 individual 16-run response surface DoEs (3 formulation × 3 press models), whose results were combined to create a polynomial regression model for each tablet property. These models predicted tablet tensile strength, porosity and disintegration time and enabled the construction of design spaces to produce tablets with specified target properties, for each formulation on each press. The models were successfully validated. This modelling approach provides an understanding of the compaction behaviour of formulations with varying deformation behaviour on development and commercial tablet press models. This understanding can be applied to inform achievable production rates at a commercial scale, during the formulation development.
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Affiliation(s)
- Raghu V. G. Peddapatla
- SSPC Pharmaceutical Research Centre, School of Pharmacy, University College Cork, T12 K8AF Cork, Ireland; (R.V.G.P.); (A.M.C.)
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
| | - Conor Slevin
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
- Pharmaceutical Manufacturing Technology Centre (PMTC), Bernal Institute, University of Limerick, V94 T9PX Limerick, Ireland;
| | - Gerard Sheridan
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
- Pharmaceutical Manufacturing Technology Centre (PMTC), Bernal Institute, University of Limerick, V94 T9PX Limerick, Ireland;
| | - Caoimhe Beirne
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
| | | | - Ivan Browning
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
| | - Clare O’Reilly
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
| | - Zelalem A. Worku
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
| | - David Egan
- Pharmaceutical Manufacturing Technology Centre (PMTC), Bernal Institute, University of Limerick, V94 T9PX Limerick, Ireland;
| | - Stephen Sheehan
- Alkermes Pharma Ireland Limited, N37 EA09 Athlone, Ireland; (C.S.); (G.S.); (C.B.); (I.B.); (C.O.); (Z.A.W.)
- Correspondence: ; Tel.: +353-877-413-140
| | - Abina M. Crean
- SSPC Pharmaceutical Research Centre, School of Pharmacy, University College Cork, T12 K8AF Cork, Ireland; (R.V.G.P.); (A.M.C.)
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Modeling of High-Density Compaction of Pharmaceutical Tablets Using Multi-Contact Discrete Element Method. Pharmaceutics 2021; 13:pharmaceutics13122194. [PMID: 34959475 PMCID: PMC8707439 DOI: 10.3390/pharmaceutics13122194] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 12/11/2021] [Accepted: 12/14/2021] [Indexed: 11/16/2022] Open
Abstract
The purpose of this work is to simulate the powder compaction of pharmaceutical materials at the microscopic scale in order to better understand the interplay of mechanical forces between particles, and to predict their compression profiles by controlling the microstructure. For this task, the new framework of multi-contact discrete element method (MC-DEM) was applied. In contrast to the conventional discrete element method (DEM), MC-DEM interactions between multiple contacts on the same particle are now explicitly taken into account. A new adhesive elastic-plastic multi-contact model invoking neighboring contact interaction was introduced and implemented. The uniaxial compaction of two microcrystalline cellulose grades (Avicel® PH 200 (FMC BioPolymer, Philadelphia, PA, USA) and Pharmacel® 102 (DFE Pharma, Nörten-Hardenberg, Germany) subjected to high confining conditions was studied. The objectives of these simulations were: (1) to investigate the micromechanical behavior; (2) to predict the macroscopic behavior; and (3) to develop a methodology for the calibration of the model parameters needed for the MC-DEM simulations. A two-stage calibration strategy was followed: first, the model parameters were directly measured at the micro-scale (particle level) and second, a meso-scale calibration was established between MC-DEM parameters and compression profiles of the pharmaceutical powders. The new MC-DEM framework could capture the main compressibility characteristics of pharmaceutical materials and could successfully provide predictions on compression profiles at high relative densities.
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