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20 pages, 3753 KiB  
Article
Twin Screw Melt Granulation of Simvastatin: Drug Solubility and Dissolution Rate Enhancement Using Polymer Blends
by Rasha M. Elkanayati, Indrajeet Karnik, Prateek Uttreja, Nagarjuna Narala, Sateesh Kumar Vemula, Krizia Karry and Michael A. Repka
Pharmaceutics 2024, 16(12), 1630; https://doi.org/10.3390/pharmaceutics16121630 - 23 Dec 2024
Abstract
Background/Objectives: This study evaluates the efficacy of twin screw melt granulation (TSMG), and hot-melt extrusion (HME) techniques in enhancing the solubility and dissolution of simvastatin (SIM), a poorly water-soluble drug with low bioavailability. Additionally, the study explores the impact of binary polymer blends [...] Read more.
Background/Objectives: This study evaluates the efficacy of twin screw melt granulation (TSMG), and hot-melt extrusion (HME) techniques in enhancing the solubility and dissolution of simvastatin (SIM), a poorly water-soluble drug with low bioavailability. Additionally, the study explores the impact of binary polymer blends on the drug’s miscibility, solubility, and in vitro release profile. Methods: SIM was processed with various polymeric combinations at a 30% w/w drug load, and a 1:1 ratio of binary polymer blends, including Soluplus® (SOP), Kollidon® K12 (K12), Kollidon® VA64 (KVA), and Kollicoat® IR (KIR). The solid dispersions were characterized using modulated differential scanning calorimetry (M-DSC), powder X-ray diffraction (PXRD), and Fourier-transform infrared spectroscopy (FTIR). Dissolution studies compared the developed formulations against a marketed product. Results: The SIM-SOP/KIR blend showed the highest solubility (34 µg/mL), achieving an approximately 5.5-fold enhancement over the pure drug. Dissolution studies showed that SIM-SOP/KIR formulations had significantly higher release profiles than the physical mixture (PM) and pure drug (p < 0.01). Additionally, their release was similar to a marketed formulation, with 100% drug release within 30 min. In contrast, the SIM-K12/KIR formulation exhibited strong miscibility, but limited solubility and slower release rates, suggesting that high miscibility does not necessarily correlate with improved solubility. Conclusions: This study demonstrates the effectiveness of TSMG, and HME as effective continuous manufacturing technologies for improving the therapeutic efficacy of poorly water-soluble drugs. It also emphasizes the complexity of polymer–drug interactions and the necessity of carefully selecting compatible polymers to optimize the quality and performance of pharmaceutical formulations. Full article
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<p>M-DSC analysis for SIM and the PMs.</p>
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<p>Equilibrium solubility of SIM in water and 1% polymer solutions.</p>
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<p>SIM dissolution from the SD extrudates after 10, 30, and 60 min.</p>
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<p>Developed granules with SOP/KIR blend using TSMG.</p>
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<p>DSC thermograms for SIM, polymers, selected SDGs, and PMs.</p>
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<p>PXRD for SIM, polymers, selected SDGs, and PMs.</p>
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<p>SEM images showing surface morphology of (<b>A</b>) simvastatin crystals (×1500), (<b>B</b>) SIM-K12/KIR PM (×500), and (<b>C</b>) (×100), (<b>D</b>) (×250) SIM-K12/KIR granules.</p>
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<p>FTIR for SIM, PMS, and selected SDGs.</p>
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<p>Dissolution profiles of crystalline SIM, PMS, and SDGs at 37 °C ± 0.5 °C in pH 7 phosphate buffer using 0.2% <span class="html-italic">w</span>/<span class="html-italic">v</span> SDS.</p>
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<p>In vitro release profiles of SOP/KIR granules and extrudates versus the marketed formulation at 37 °C ± 0.5 °C in pH 7 phosphate buffer using 0.2% <span class="html-italic">w</span>/<span class="html-italic">v</span> SDS.</p>
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12 pages, 7365 KiB  
Article
Dry Amorphization of Itraconazole Using Mesoporous Silica and Twin-Screw Technology
by Margarethe Richter, Simon Welzmiller, Fred Monsuur, Annika R. Völp and Joachim Quadflieg
Pharmaceutics 2024, 16(11), 1368; https://doi.org/10.3390/pharmaceutics16111368 - 25 Oct 2024
Viewed by 828
Abstract
Background/Objectives: Amorphization of an active pharmaceutical ingredient (API) can improve its dissolution and enhance bioavailability. Avoiding solvents for drug amorphization is beneficial due to environmental issues and potential solvent residues in the final product. Methods: Dry amorphization using a twin-screw extruder is presented [...] Read more.
Background/Objectives: Amorphization of an active pharmaceutical ingredient (API) can improve its dissolution and enhance bioavailability. Avoiding solvents for drug amorphization is beneficial due to environmental issues and potential solvent residues in the final product. Methods: Dry amorphization using a twin-screw extruder is presented in this paper. A blend of mesoporous silica particles and crystalline itraconazole was processed using a pharma-grade laboratory scale twin-screw extruder. The influence of different screw configurations and process parameters was tested. Particle size and shape are compared in scanning electron microscopy (SEM) images. Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) are used to determine the residual amount of crystalline itraconazole in the final product. Results: An optimized screw configuration for the process was found which leads to more than 90% amorphous API when processed at room temperature. Full amorphization was reached at 70 °C. The specific mechanic energy (SME) introduced into the material during twin-screw processing is crucial for the dry amorphization. The higher the SME, the lower the residual amount of crystalline API. Two months after processing, however, recrystallization was observed by XRD. Conclusions: Dry processing using a twin-screw extruder is continuous, free of solvents and can be performed at low temperatures. This study proves the concept of twin-screw processing with mesoporous silica for dry amorphization of itraconazole. Full article
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<p>Screw configurations sc1 to sc4 for the Pharma 11 extruder in TSG mode.</p>
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<p>DSC results for processed material with screw configuration sc1, at a screw speed of 30 rpm, a throughput of 0.1 kg/h, and different processing temperatures (20, 100, and 200 °C).</p>
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<p>DSC results for processed material with screw configuration sc2.</p>
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<p>DSC results for processed material with screw configuration sc4. DSC measurement 1 month after processing.</p>
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<p>SEM images of (<b>A</b>) pure itraconazole, (<b>B</b>) pre-blend of mesoporous silica and itraconazole, granules produced by twin-screw granulation at (<b>C</b>) 25 °C, 100 rpm screw speed and 0.1 kg/h throughput, and (<b>D</b>) at 25 °C, 250 rpm screw speed and 0.5 kg/h throughput. Unprocessed SEM pictures can be found in the <a href="#app1-pharmaceutics-16-01368" class="html-app">Supplementary Figure S2A–D</a>.</p>
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<p>XRD patterns of samples of mesoporous silica and itraconazole produced by twin-screw granulation at (<b>A</b>) 25 °C, 250 rpm screw speed, and 0.5 kg/h throughput, and (<b>B</b>) 70 °C, 250 rpm screw speed, and 0.5 kg/h throughput.</p>
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<p>Crystallinity of API over the specific mechanical energy introduced during the twin-screw process with different screw configurations at room temperature.</p>
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18 pages, 3054 KiB  
Article
Understanding Powder Behavior in Continuous Feeding: Powder Densification and Screw Layering
by Sara Fathollahi, Pauline H. M. Janssen, Bram Bekaert, Dirk Vanderroost, Valerie Vanhoorne and Bastiaan H. J. Dickhoff
Powders 2024, 3(4), 482-499; https://doi.org/10.3390/powders3040026 - 30 Sep 2024
Viewed by 823
Abstract
Background: Precise continuous feeding of active pharmaceutical ingredients (APIs) and excipients is crucial in a continuous powder-to-tablet manufacturing setup, as any inconsistency can affect the final tablet quality. Method: This study investigated the impact of various materials on the performance of a continuous [...] Read more.
Background: Precise continuous feeding of active pharmaceutical ingredients (APIs) and excipients is crucial in a continuous powder-to-tablet manufacturing setup, as any inconsistency can affect the final tablet quality. Method: This study investigated the impact of various materials on the performance of a continuous twin-screw loss-in-weight (LIW) feeder. The materials tested included spray-dried lactose, anhydrous lactose, granulated lactose, microcrystalline cellulose (MCC), an MCC–lactose preblend (50%:50% w/w ratio), and a co-processed excipient (lactose–lactitol at a 95%:5% w/w ratio). The feeding performance of these excipients was systematically assessed, focusing on powder densification and screw layering within the LIW feeder. Results: The results demonstrated densification for the spray-dried lactose and preblend. Densification was more pronounced during the initial feeding cycles for spray-dried lactose, but decreased gradually over time. In contrast, the densification remained relatively constant throughout the feeding process for the preblend. Notably, minor screw layering was observed for both spray-dried lactose and anhydrous lactose, with the extent of this issue reducing over time for the spray-dried lactose. Interestingly, granulated lactose grades did not show screw layering, making them preferable for blending with APIs prone to severe screw layering. The LIW feeder control system successfully managed powder densification and minor screw layering, maintaining the mass flow rate at the set point for all investigated materials. Conclusions: These findings inform the selection of optimal excipients, appropriate tooling for LIW feeders, and the enhancement of control strategies to shorten startup times. By addressing these factors, the precision and reliability of continuous feeding processes can be improved. Full article
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<p>Schematic of the continuous direct compression line investigated in this study.</p>
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<p>Schematic illustrating the feeding cycles between two consecutive refills (highlighted in gray), and refills in continuous feeding.</p>
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<p>Schematic illustrating the phenomena of densification and screw layering in continuous feeding. The light green lines indicate screw layering, and the yellow arrows show densification. (<b>a</b>) No densification, no screw layering, (<b>b</b>) no densification, but screw layering, (<b>c</b>) densification, no screw layering, (<b>d</b>) densification and screw layering.</p>
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<p>Feeding of 11SD (<b>top</b>) and 22AN (<b>bottom</b>). The blue dots represent FF per second. Gray regions indicate recognized feeding cycles. The dotted black lines indicate the degree of powder densification in the feeder hopper. The solid black line reflects screw layering during continuous feeding.</p>
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<p>Feeding of 24AN (<b>top</b>), 30GR (<b>middle</b>), and 40LL (<b>bottom</b>). The blue dots represent FF per second. Gray regions indicate recognized feeding cycles. The dotted black lines indicate the degree of powder densification in the feeder hopper. The solid black line reflects screw layering during continuous feeding.</p>
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<p>Feeding of PH102 and preblend (PH102:24AN with 50:50% <span class="html-italic">w</span>/<span class="html-italic">w</span>). The blue dots represent FF per second. Gray regions indicate recognized feeding cycles. The dotted black lines indicate the degree of powder densification in the feeder hopper. The solid black line reflects screw layering during continuous feeding.</p>
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<p>Summary of statistically quantified densification for the investigated materials.</p>
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<p>Summary of statistically quantified screw layering for the investigated materials.</p>
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20 pages, 2426 KiB  
Article
Evaluation of Polyvinyl Alcohol as Binder during Continuous Twin Screw Wet Granulation
by Phaedra Denduyver, Gudrun Birk, Alessandra Ambruosi, Chris Vervaet and Valérie Vanhoorne
Pharmaceutics 2024, 16(7), 854; https://doi.org/10.3390/pharmaceutics16070854 - 25 Jun 2024
Viewed by 1954
Abstract
Binder selection is a crucial step in continuous twin-screw wet granulation (TSWG), as the material experiences a much shorter residence time (2–40 s) in the granulator barrel compared to batch-wise granulation processes. Polyvinyl alcohol (PVA) 4-88 was identified as an effective binder during [...] Read more.
Binder selection is a crucial step in continuous twin-screw wet granulation (TSWG), as the material experiences a much shorter residence time (2–40 s) in the granulator barrel compared to batch-wise granulation processes. Polyvinyl alcohol (PVA) 4-88 was identified as an effective binder during TSWG, but the potential of other PVA grades—differing in polymerization and hydrolysis degree—has not yet been studied. Therefore, the aim of the current study was to evaluate the potential of different PVA grades as a binder during TSWG. The breakage and drying behavior during the fluidized bed drying of drug-loaded granules containing the PVA grades was also studied. Three PVA grades (4-88, 18-88, and 40-88) were characterized and their attributes were compared to previously investigated binders by Vandevivere et al. through principal component analysis. Three binder clusters could be distinguished according to their attributes, whereby each cluster contained a PVA grade and a previously investigated binder. PVA 4-88 was the most effective binder of the PVA grades for both a good water-soluble and water-insoluble formulation. This could be attributed to its high total surface energy, low viscosity, good wettability of hydrophilic and hydrophobic surfaces, and good wettability by water of the binder. Compared to the previously investigated binders, all PVA grades were more effective in the water-insoluble formulation, as they yielded strong granules (friability below 30%) at lower L/S-ratios. This was linked to the high dispersive surface energy of the high-energy sites on the surface of PVA grades and their low surface tension. During fluidized bed drying, PVA grades proved suitable binders, as the acetaminophen (APAP) granules were dried within a short time due to the low L/S-ratio, at which high-quality granules could be produced. In addition, no attrition occurred, and strong tablets were obtained. Based on this study, PVA could be the preferred binder during twin screw granulation due to its high binder effectiveness at a low L/S-ratio, allowing efficient downstream processing. However, process robustness must be controlled by the included excipients, as PVA grades are operating in a narrow L/S-ratio range. Full article
(This article belongs to the Special Issue Impact of Raw Material Properties on Solid Dosage Form Processes)
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Graphical abstract

Graphical abstract
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<p>Screw configuration with material flow from left to right. Kneading zones consist of 6 kneading elements (length-to-diameter (L/D) 1/4) in a stagger angle of 60°. Granulation liquid was added just before the first kneading zone.</p>
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<p>The score (<b>a</b>) and loading (<b>b</b>) scatter plot of PC 1 versus PC 2. The different colors refer to the binder clusters, which have comparable binder attributes. Cluster 1 (red) contains PVA 4-88 and SOS CO01; cluster 2 (yellow) has PVA 18-88 and PVP K90; cluster 3 (blue) has PVA 40-88 and HPMC E15; and cluster 4 (green) has maltodextrin 6, HP pea starch, PVP K12, and PVP K30.</p>
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<p>The dispersive (<b>top</b>), specific (<b>middle</b>) and total (<b>bottom</b>) surface energy in the function of the fractional coverage for cluster 1, 2, and 3 binders. The specific and total surface energies of HPMC E15 could not be measured due to weak solvent interactions.</p>
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<p>SME values in function of the L/S-ratio for each binder in mannitol- and DCP-based formulations. L/S-ratios depicted are based on the L/S-ratio range from <a href="#pharmaceutics-16-00854-t001" class="html-table">Table 1</a>.</p>
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<p>Friability in function of the L/S-ratio for each binder in the mannitol- and DCP-based formulations. The L/S-ratios depicted are based on the L/S-ratio range from <a href="#pharmaceutics-16-00854-t001" class="html-table">Table 1</a>.</p>
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<p>Moisture content of the granules in function of drying time. Granules were produced on the L/S-ratio mentioned in <a href="#pharmaceutics-16-00854-t003" class="html-table">Table 3</a>.</p>
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<p>Breakage behavior of APAP granules with PVA grades. Solid line represents the particle size distribution of tray-dried granules (TDG). Dashed and dotted lines represent the particle size distribution after fluid bed drying at first and second drying times, respectively.</p>
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<p>Tensile strength in function of main compaction pressure for studied binders in APAP formulation.</p>
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34 pages, 1507 KiB  
Review
Process Simulation of Twin-Screw Granulation: A Review
by Tony Bediako Arthur and Nejat Rahmanian
Pharmaceutics 2024, 16(6), 706; https://doi.org/10.3390/pharmaceutics16060706 - 24 May 2024
Cited by 1 | Viewed by 3891
Abstract
Twin-screw granulation has emerged as a key process in powder processing industries and in the pharmaceutical sector to produce granules with controlled properties. This comprehensive review provides an overview of the simulation techniques and approaches that have been employed in the study of [...] Read more.
Twin-screw granulation has emerged as a key process in powder processing industries and in the pharmaceutical sector to produce granules with controlled properties. This comprehensive review provides an overview of the simulation techniques and approaches that have been employed in the study of twin-screw granulation processes. This review discusses the major aspects of the twin-screw granulation process which include the fundamental principles of twin-screw granulation, equipment design, process parameters, and simulation methodologies. It highlights the importance of operating conditions and formulation designs in powder flow dynamics, mixing behaviour, and particle interactions within the twin-screw granulator for enhancing product quality and process efficiency. Simulation techniques such as the population balance model (PBM), computational fluid dynamics (CFD), the discrete element method (DEM), process modelling software (PMS), and other coupled techniques are critically discussed with a focus on simulating twin-screw granulation processes. This paper examines the challenges and limitations associated with each simulation approach and provides insights into future research directions. Overall, this article serves as a valuable resource for researchers who intend to develop their understanding of twin-screw granulation and provides insights into the various techniques and approaches available for simulating the twin-screw granulation process. Full article
(This article belongs to the Special Issue Pharmaceutical Solids: Advanced Manufacturing and Characterization)
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<p>A schematic of a continuous twin-screw granulation [<a href="#B2-pharmaceutics-16-00706" class="html-bibr">2</a>].</p>
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<p>Twin-screw element, from Aftab (2018) [<a href="#B31-pharmaceutics-16-00706" class="html-bibr">31</a>].</p>
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<p>Schematic of simulation workflow.</p>
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27 pages, 4839 KiB  
Article
Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map
by Lalith Kotamarthy, Subhodh Karkala, Ashley Dan, Andrés D. Román-Ospino and Rohit Ramachandran
Pharmaceutics 2024, 16(4), 456; https://doi.org/10.3390/pharmaceutics16040456 - 25 Mar 2024
Viewed by 1579
Abstract
Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing [...] Read more.
Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism. Full article
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<p>Fill level estimated vs. fill level reported in earlier studies. Orange dotted line (<span style="color:#FE9A2E">......</span>) represents the x = y line, green dots (<span style="color:#74DF00"><sup>◆</sup></span>) represent the estimated fill level values, and black dotted lines (<b>- -</b>) represent the 5% error margins.</p>
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<p>(<b>a</b>) Effect of screw speed on RTD, (<b>b</b>) effect of screw speed on PSD, and (<b>c</b>) effect of screw speed on content uniformity.</p>
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<p>Effect of screw speed on the granule microstructure: (<b>a</b>) 300 rpm, (<b>b</b>) 500 rpm, and (<b>c</b>) 700 rpm.</p>
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<p>Microstructure investigation of the granule obtained at a screw speed of 300 rpm.</p>
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<p>Effect of the number of kneading elements on the (<b>a</b>) residence time distribution, (<b>b</b>) particle size distribution, and (<b>c</b>) content uniformity.</p>
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<p>Effects of kneading elements on the granule microstructure: (<b>a</b>) 0 kneading elements/all conveying elements, (<b>b</b>) 2 kneading elements, (<b>c</b>) 4 kneading elements, (<b>d</b>) 6 kneading elements, and (<b>e</b>) 8 kneading elements.</p>
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<p>Positions of the kneading zone relative to the liquid addition zone used in this study.</p>
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<p>Effect of the kneading zone position on the (<b>a</b>) residence time distribution, (<b>b</b>) particle size distribution, and (<b>c</b>) content uniformity.</p>
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<p>Effect of the kneading zone position on the granule microstructure in (<b>a</b>) zone 4, (<b>b</b>) zone 5, (<b>c</b>) zone 6.</p>
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<p>Different stages of liquid saturation in a granule [<a href="#B60-pharmaceutics-16-00456" class="html-bibr">60</a>].</p>
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<p>Mechanistic process map depicting the effects of input parameters on granule quality attributes through mixing and granulation growth mechanisms (red circles represent API particles, black circles represent excipient particles ad blue line over particle clusters represents surface water layer).</p>
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12 pages, 3676 KiB  
Article
Studying the API Distribution of Controlled Release Formulations Produced via Continuous Twin-Screw Wet Granulation: Influence of Matrix Former, Filler and Process Parameters
by Phaedra Denduyver, Chris Vervaet and Valérie Vanhoorne
Pharmaceutics 2024, 16(3), 341; https://doi.org/10.3390/pharmaceutics16030341 - 28 Feb 2024
Viewed by 1571
Abstract
Hydroxypropyl methylcellulose (HPMC) is a preferred hydrophilic matrix former for controlled release formulations produced through continuous twin-screw wet granulation. However, a non-homogeneous API distribution over sieve fractions with underdosing in the fines fraction (<150 µm) was previously reported. This could result in content [...] Read more.
Hydroxypropyl methylcellulose (HPMC) is a preferred hydrophilic matrix former for controlled release formulations produced through continuous twin-screw wet granulation. However, a non-homogeneous API distribution over sieve fractions with underdosing in the fines fraction (<150 µm) was previously reported. This could result in content uniformity issues during downstream processing. Therefore, the current study investigated the root cause of the non-homogeneous theophylline distribution. The effect of process parameters (L/S-ratio and screw configuration) and formulation parameters (matrix former and filler type) on content uniformity was studied. Next, the influence of the formulation parameters on tableting and dissolution behavior was investigated. Altering the L/S-ratio or using a more aggressive screw configuration did not result in a homogeneous API distribution over the granule sieve fractions. Using microcrystalline cellulose (MCC) as filler improved the API distribution due to its similar behavior as HPMC. As excluding HPMC or including a hydrophobic matrix former (Kollidon SR) yielded granules with a homogeneous API distribution, HPMC was identified as the root cause of the non-homogeneous API distribution. This was linked to its fast hydration and swelling (irrespective of the HPMC grade) upon addition of the granulation liquid. Full article
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<p>Screw configuration 1 with material flow from left to right. Kneading zones consists of 6 kneading elements (length-to-diameter ratio 1/4) in a stagger angle of 60°. In screw configuration 2 and 3, one and two kneading elements were placed in angle of 90°, respectively. Granulation liquid was added just before first kneading zone.</p>
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<p>Torque profiles with matrix formers HPMC type 2208, HPMC type 2906, Kollidon SR and without matrix former. While a common L/S-ratio was used for HPMC-based formulations, the L/S-ratio was adapted for formulations containing Kollidon SR and without matrix former to avoid processing issues.</p>
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<p>Theophylline recovery (% of theoretical content) in function of granule sieve fraction, when processed at low (dashed line) and high (full line) L/S-ratio using SC1 (orange), SC2 (green) or SC3 (blue).</p>
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<p>Formulations without matrix former (20% <span class="html-italic">w</span>/<span class="html-italic">w</span> theophylline and 80% <span class="html-italic">w</span>/<span class="html-italic">w</span> filler). Figures show theophylline recovery (% of theoretical content) as a function of the granule sieve fractions at low and high L/S-ratio, respectively.</p>
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<p>Theophylline recovery (% of theoretical content) in function of the sieve fraction for formulations with HPMC type 2906 and 2208 as matrix former at low and high L/S-ratio.</p>
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<p>Theophylline recovery (% of theoretical content) in function of granule sieve fraction for formulations with Kollidon SR as matrix former at low and high L/S-ratio.</p>
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<p>Tabletability and dissolution profile of tablets produced with theophylline as drug, HPMC type 2208, HPMC type 2906 or Kollidon SR as matrix former and DCP or MCC as filler. Tablets for dissolution were compressed at 318 MPa.</p>
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15 pages, 4237 KiB  
Article
Integrated Continuous Wet Granulation and Drying: Process Evaluation and Comparison with Batch Processing
by Seth P. Forster, Erin Dippold, Abbe Haser, Daniel Emanuele and Robin Meier
Pharmaceutics 2023, 15(9), 2317; https://doi.org/10.3390/pharmaceutics15092317 - 14 Sep 2023
Cited by 1 | Viewed by 3825
Abstract
The pharmaceutical industry is in the midst of a transition from traditional batch processes to continuous manufacturing. However, the challenges in making this transition vary depending on the selected manufacturing process. Compared with other oral solid dosage processes, wet granulation has been challenging [...] Read more.
The pharmaceutical industry is in the midst of a transition from traditional batch processes to continuous manufacturing. However, the challenges in making this transition vary depending on the selected manufacturing process. Compared with other oral solid dosage processes, wet granulation has been challenging to move towards continuous processing since traditional equipment has been predominantly strictly batch, instead of readily adapted to material flow such as dry granulation or tablet compression, and there have been few equipment options for continuous granule drying. Recently, pilot and commercial scale equipment combining a twin-screw wet granulator and a novel horizontal vibratory fluid-bed dryer have been developed. This study describes the process space of that equipment and compares the granules produced with batch high-shear and fluid-bed wet granulation processes. The results of this evaluation demonstrate that the equipment works across a range of formulations, effectively granulates and dries, and produces granules of similar or improved quality to batch wet granulation and drying. Full article
(This article belongs to the Special Issue Pharmaceutical Continuous Manufacturing: Then and Now)
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<p>(<b>a</b>) QbCon 1 granulator and dryer equipment, (<b>b</b>) point of transfer to continuous dryer, (<b>c</b>) continuous dryer showing limited back-mixing between process conditions.</p>
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<p>Screw profile used for TSWG on QbCon1. D = Diameter, indicating how the length of the screw element compares with the granulator screw diameter; KB = kneading block element; CM = combing element.</p>
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<p>(<b>a</b>) Mean granule size by L/S; (<b>b</b>) Mean granule size by ST; (<b>c</b>) Mean granule size by SMESEM.</p>
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<p>(<b>a</b>) Mean granule size by L/S; (<b>b</b>) Mean granule size by ST; (<b>c</b>) Mean granule size by SMESEM.</p>
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<p>Scanning electron micrographs of (<b>a</b>) placebo granules, Run #37; (<b>b</b>) MK-B, Run #4; (<b>c</b>) MK-B, Run #6; (<b>d</b>) MK-A Run #1; (<b>e</b>) MK-A Run #2, all 250×. (<b>f</b>) MK-A FBG, 100×.</p>
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<p>Scanning electron micrographs of (<b>a</b>) placebo granules, Run #37; (<b>b</b>) MK-B, Run #4; (<b>c</b>) MK-B, Run #6; (<b>d</b>) MK-A Run #1; (<b>e</b>) MK-A Run #2, all 250×. (<b>f</b>) MK-A FBG, 100×.</p>
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<p>Tabletability of (<b>a</b>) 10% <span class="html-italic">w</span>/<span class="html-italic">w</span> MCC and (<b>b</b>) 20% <span class="html-italic">w</span>/<span class="html-italic">w</span> MCC placebo granules made with the QbCon1.</p>
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<p>Comparing the tabletability of MK-A granulations made by continuous and batch wet granulation techniques.</p>
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<p>Comparing the tabletability of MK-B granulations made by continuous and batch wet granulation techniques.</p>
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25 pages, 4505 KiB  
Article
Twin Screw Melt Granulation: A Single Step Approach for Developing Self-Emulsifying Drug Delivery System for Lipophilic Drugs
by Dinesh Nyavanandi, Preethi Mandati, Sagar Narala, Abdullah Alzahrani, Praveen Kolimi, Sateesh Kumar Vemula and Michael A. Repka
Pharmaceutics 2023, 15(9), 2267; https://doi.org/10.3390/pharmaceutics15092267 - 1 Sep 2023
Cited by 11 | Viewed by 1657
Abstract
The current research aims to improve the solubility of the poorly soluble drug, i.e., ibuprofen, by developing self-emulsifying drug delivery systems (SEDDS) utilizing a twin screw melt granulation (TSMG) approach. Gelucire® 44/14, Gelucire® 48/16, and Transcutol® HP were screened as [...] Read more.
The current research aims to improve the solubility of the poorly soluble drug, i.e., ibuprofen, by developing self-emulsifying drug delivery systems (SEDDS) utilizing a twin screw melt granulation (TSMG) approach. Gelucire® 44/14, Gelucire® 48/16, and Transcutol® HP were screened as suitable excipients for developing the SEDDS formulations. Initially, liquid SEDDS (L-SEDDS) were developed with oil concentrations between 20–50% w/w and surfactant to co-surfactant ratios of 2:1, 4:1, 6:1. The stable formulations of L-SEDDS were transformed into solid SEDDS (S-SEDDS) using a suitable adsorbent carrier and compressed into tablets (T-SEDDS). The S-SEDDS has improved flow, drug release profiles, and permeability compared to pure drugs. The existence of the drug in an amorphous state was confirmed by differential scanning calorimetry (DSC) and powder X-ray diffraction analysis (PXRD). The formulations with 20% w/w and 30% w/w of oil concentration and a 4:1 ratio of surfactant to co-surfactant have resulted in a stable homogeneous emulsion with a globule size of 14.67 ± 0.23 nm and 18.54 ± 0.55 nm. The compressed tablets were found stable after six months of storage at accelerated and long-term conditions. This shows the suitability of the TSMG approach as a single-step continuous manufacturing process for developing S-SEDDS formulations. Full article
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<p>Solubility of the drug (ibuprofen) in various lipid excipients. The solubility is represented as the amount of drug dissolved in one gram of lipid.</p>
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<p>Ternary phase diagram representing emulsification region (black box) among the investigated concentrations. The green circled points represent the stable formulation after 48 h of storage at ambient temperature.</p>
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<p>Thermal properties of pure drug, physical mixtures, pure excipients, and granules of S1 and S2 formulations.</p>
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<p>Hot-stage microscopy representing the solubilizing capacity of the lipid excipients. S1 and S2 represents the granule formulations.</p>
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<p>PXRD diffractograms of pure drug, Neusilin<sup>®</sup> US2, Gelucire<sup>®</sup> 44/14, Gelucire<sup>®</sup> 48/16, and granules of S-SEDDS formulations (S1 &amp; S2).</p>
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<p>FTIR spectra of pure drug, Neusilin<sup>®</sup> US2, Gelucire<sup>®</sup> 44/14, Gelucire<sup>®</sup> 48/16, and granules of S-SEDDS formulations (S1 &amp; S2) (X-axis: wavenumber; Y-axis: absorbance).</p>
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<p>Scanning electron microscopy analysis for the (<b>A</b>) pure active substance, Ibuprofen (×200 magnification) (<b>B</b>) pure solid adsorbent carrier Neusilin<sup>®</sup> US2 (×300 magnification) (<b>C</b>) granules of S-SEDDS; S1 (×180 magnification) (<b>D</b>) granules of S-SEDDS; S2 (×650 magnification).</p>
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<p>TEM images of S-SEDDS formulations (S1, S2). (<b>A</b>) Formulation S1 (<b>B</b>) Formulation S2.</p>
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<p>In vitro drug release profiles of S - SEDDS granules in (<b>A</b>) water, (<b>B</b>) 0.1N HCl, and (<b>C</b>) pH 7.2 phosphate buffer solution (PBS).</p>
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<p>In vitro diffusion studies of S-SEDDS formulations (S1, S2) in comparison with pure drug.</p>
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13 pages, 3255 KiB  
Article
Material Transport Characteristics in Planetary Roller Melt Granulation
by Tom Lang, Andreas Bramböck, Markus Thommes and Jens Bartsch
Pharmaceutics 2023, 15(8), 2039; https://doi.org/10.3390/pharmaceutics15082039 - 28 Jul 2023
Cited by 4 | Viewed by 1165
Abstract
Melt granulation for improving material handling by modifying particle size distribution offers significant advantages compared to the standard methods of dry and wet granulation in dust reduction, obviating a subsequent drying step. Furthermore, current research in pharmaceutical technology aims for continuous methods, as [...] Read more.
Melt granulation for improving material handling by modifying particle size distribution offers significant advantages compared to the standard methods of dry and wet granulation in dust reduction, obviating a subsequent drying step. Furthermore, current research in pharmaceutical technology aims for continuous methods, as these have an enhanced potential to reduce product quality fluctuations. Concerning both aspects, the use of a planetary roller granulator is consequential. The process control with these machines benefits from the enhanced ratio of heated surface to processed volume, compared to the usually-applied twin-screw systems. This is related to the unique concept of planetary spindles flowing around a central spindle in a roller cylinder. Herein, the movement pattern defines the transport characteristics, which determine the energy input and overall processing conditions. The aim of this study is to investigate the residence time distribution in planetary roller melt granulation (PRMG) as an indicator for the material transport. By altering feed rate and rotation speed, the fill level in the granulator is adjusted, which directly affects the average transport velocity and mixing volume. The two-compartment model was utilized to reflect these coherences, as the model parameters symbolize the sub-processes of axial material transport and mixing. Full article
(This article belongs to the Special Issue Pharmaceutical Continuous Manufacturing: Then and Now)
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<p>Radial cross-section of planetary roller processing section, including central spindle, planetary spindle, and roller cylinder. The heating of the roller cylinder and central spindle is independent. The central spindle, in addition to the number of planetary spindles, determines the free radial cross-section and free processing volume in axial direction.</p>
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<p>Typical profile of the residence time density function and corresponding cumulative form, including characteristic parameters.</p>
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<p>Setup for non-destructive on-line determination of residence time distribution in planetary roller melt granulation experiments via ExtruVis system. Camera sensor placed in front of granulator discharge blend.</p>
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<p>Experimentally determined residence time distribution in steady state at four fixed parameter sets, representing the investigated design space for the investigation of the transport characteristics in planetary roller melt granulation. For the clarity of visual data representation, only every 125th data point is plotted for each data set.</p>
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<p>Residence time distribution and model fit to the experimental data for each parameter set of the investigated design space. Granulator configuration, set temperature (central spindle, roller cylinder), and equipment were fixed for all experiments. The symbols equal the applied rotation speed; colour represents applied feed rates. For the clarity of visual data representation, only every 125th data point is plotted for each data set.</p>
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<p>Ratio of RTD median to hydrodynamic residence time as surrogate for the granulator fill level parameter for each parameter set of the investigated design space (<a href="#pharmaceutics-15-02039-f003" class="html-fig">Figure 3</a>). Granulator configuration, set temperature (central spindle, roller cylinder), and equipment were fixed for all experiments. The symbols equal the applied rotation speed, colour represents applied feed rates. Line represents the fit of a power model approach to the overall displayed data.</p>
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<p>Fitted and transformed transport and mixing-related parameters of the applied two-compartment model to the experimental data for each parameter set of the investigated design space. Granulator configuration, set temperature (central spindle, roller cylinder), and equipment were fixed for all experiments. The symbols equal the model parameter, colour represents applied feed rates. Rotation speeds decrease for higher SFL at a constant feed rate. Lines represent the fit of a linear model approach to the overall displayed data.</p>
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16 pages, 3305 KiB  
Article
Application of I-Optimal Design for Modeling and Optimizing the Operational Parameters of Ibuprofen Granules in Continuous Twin-Screw Wet Granulation
by Jie Zhao, Geng Tian and Haibin Qu
Biomedicines 2023, 11(7), 2030; https://doi.org/10.3390/biomedicines11072030 - 19 Jul 2023
Cited by 1 | Viewed by 1249
Abstract
The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) [...] Read more.
The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) ratio, TSWG feed rate, and numbers of the 30° and 60° mixing elements, on the granule quality in a TSWG process, but it can also provide a prediction of the response to determine the optimum operating conditions. Based on the constraints of the desired granule properties, a design space for the TSWG was determined, and the ranges of the operating parameters were defined. An acceptable degree of prediction was confirmed through validation experiments, demonstrating the reliability and effectiveness of using the I-optimal design method to study the TSWG process. The I-optimal design method can accelerate the screening and optimization of the TSWG process. Full article
(This article belongs to the Special Issue Novel Drug Delivery Systems: Design, Evaluation and Application)
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<p>Setup and screw configuration of TSWG.</p>
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<p>The response contour plot displays the effects of independent variables on the moisture content: (<b>a</b>–<b>c</b>) effects of <span class="html-italic">X</span><sub>1</sub> and <span class="html-italic">X</span><sub>2</sub>, (<b>d</b>–<b>f</b>) <span class="html-italic">X</span><sub>3</sub> and <span class="html-italic">X</span><sub>4</sub>, and (<b>g</b>–<b>i</b>) <span class="html-italic">X</span><sub>2</sub> and <span class="html-italic">X</span><sub>5</sub> on the moisture content while other factors were maintained at low, middle, and high levels, respectively.</p>
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<p>The response contour plot displays the effects of independent variables on the granule size D<sub>50</sub>: (<b>a</b>–<b>c</b>) effects of <span class="html-italic">X</span><sub>1</sub> and <span class="html-italic">X</span><sub>2</sub>, (<b>d</b>–<b>f</b>) <span class="html-italic">X</span><sub>2</sub> and <span class="html-italic">X</span><sub>3</sub>, and (<b>g</b>–<b>i</b>) <span class="html-italic">X</span><sub>2</sub> and <span class="html-italic">X</span><sub>4</sub> on the granule size D<sub>50</sub> while other factors were maintained at low, middle, and high levels, respectively.</p>
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<p>The response contour plot displays the effects of independent variables on the span: (<b>a</b>–<b>c</b>) effects of <span class="html-italic">X</span><sub>1</sub> and <span class="html-italic">X</span><sub>2</sub>, (<b>d</b>–<b>f</b>) <span class="html-italic">X</span><sub>3</sub> and <span class="html-italic">X</span><sub>5</sub>, and (<b>g</b>–<b>i</b>) <span class="html-italic">X</span><sub>2</sub> and <span class="html-italic">X</span><sub>4</sub> on the span while other factors were maintained at low, middle, and high levels, respectively.</p>
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<p>The response contour plot displays the effects of independent variables on the production yield: (<b>a</b>–<b>c</b>) effects of <span class="html-italic">X</span><sub>1</sub> and <span class="html-italic">X</span><sub>2</sub>, (<b>d</b>–<b>f</b>) <span class="html-italic">X</span><sub>3</sub> and <span class="html-italic">X</span><sub>5</sub>, and (<b>g</b>–<b>i</b>) <span class="html-italic">X</span><sub>4</sub> and <span class="html-italic">X</span><sub>5</sub> on the production yield while other factors were maintained at low, middle, and high levels, respectively.</p>
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<p>Design space for TSWG from different viewpoints.</p>
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16 pages, 822 KiB  
Review
Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation
by Jie Zhao, Geng Tian and Haibin Qu
Biomedicines 2023, 11(7), 1923; https://doi.org/10.3390/biomedicines11071923 - 6 Jul 2023
Cited by 4 | Viewed by 2662
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Novel Drug Delivery Systems: Design, Evaluation and Application)
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<p>Ishikawa diagram for the twin-screw granulation process behavior.</p>
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<p>Schematic of the models for granulation.</p>
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18 pages, 6077 KiB  
Article
Towards the Continuous Manufacturing of Liquisolid Tablets Containing Simethicone and Loperamide Hydrochloride with the Use of a Twin-Screw Granulator
by Daniel Zakowiecki, Margarethe Richter, Ceren Yuece, Annika Voelp, Maximilian Ries, Markos Papaioannou, Peter Edinger, Tobias Hess, Krystyna Mojsiewicz-Pieńkowska and Krzysztof Cal
Pharmaceutics 2023, 15(4), 1265; https://doi.org/10.3390/pharmaceutics15041265 - 18 Apr 2023
Cited by 1 | Viewed by 2872
Abstract
Continuous manufacturing is becoming the new technological standard in the pharmaceutical industry. In this work, a twin-screw processor was employed for the continuous production of liquisolid tablets containing either simethicone or a combination of simethicone with loperamide hydrochloride. Both active ingredients present major [...] Read more.
Continuous manufacturing is becoming the new technological standard in the pharmaceutical industry. In this work, a twin-screw processor was employed for the continuous production of liquisolid tablets containing either simethicone or a combination of simethicone with loperamide hydrochloride. Both active ingredients present major technological challenges, as simethicone is a liquid, oily substance, and loperamide hydrochloride was used in a very small amount (0.27% w/w). Despite these difficulties, the use of porous tribasic calcium phosphate as a carrier and the adjustment of the settings of the twin-screw processor enabled the optimization of the characteristics of the liquid-loaded powders and made it possible to efficiently produce liquisolid tablets with advantages in physical and functional properties. The application of chemical imaging by means of Raman spectroscopy allowed for the visualization of differences in the distribution of individual components of the formulations. This proved to be a very effective tool for identifying the optimum technology to produce a drug product. Full article
(This article belongs to the Special Issue Continuous Pharmaceutical Manufacturing, Volume II)
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<p>Schematic diagram of a production line for manufacturing liquisolid tablets containing simethicone and loperamide hydrochloride.</p>
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<p>Schematic diagram of the screw configuration with one (<b>A</b>) or two (<b>B</b>) kneading zones and corresponding barrel set-up (prepared in Twin Screw Configurator software version 1.34 (6) from Thermo Fisher Scientific, Karlsruhe, Germany).</p>
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<p>Comparison of (<b>A</b>) flow properties (angle of repose) and (<b>B</b>) particle size distribution of liquid-loaded powders and placebo blend. Means of <span class="html-italic">n</span> = 3; SD is indicated by the error bars.</p>
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<p>Comparison of (<b>A</b>) hardness (breaking force); means of <span class="html-italic">n</span> = 10, (<b>B</b>) friability; means of <span class="html-italic">n</span> = 3, (<b>C</b>) disintegration time; means of <span class="html-italic">n</span> = 6 of liquisolid formulations compressed under various compression forces. SD is indicated by the error bars.</p>
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<p>Comparison of dissolution rate of loperamide hydrochloride from liquisolid formulations compressed under various compression forces. Means of <span class="html-italic">n</span> = 6; SD is indicated by the error bars.</p>
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<p>(<b>A</b>) Uniformity of dosage units and (<b>B</b>) Defoaming activity of liquisolid tablets compressed at 20 kN; means of <span class="html-italic">n</span> = 6. SD is indicated by the error bars.</p>
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<p>Raman maps of liquisolid tablets registered with 25 µm and 5 µm spatial resolutions. The spectra are separated into chemical components by MCR analysis and displayed in different colors.</p>
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<p>Raman spectra of simethicone, TCP, and an example of a spectrum recorded in the dark blue areas of the Raman correlation maps showing the superposition of individual Raman spectra.</p>
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<p>Raman correlation map showing the spatial distribution of loperamide hydrochloride; red sites are those with the highest, and blue sites are those with the lowest correlation of the Raman spectrum with that of loperamide hydrochloride.</p>
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27 pages, 2850 KiB  
Article
Analysis of the Influence of Process and Formulation Properties on the Drying Behavior of Pharmaceutical Granules in a Semi-Continuous Fluid Bed Drying System
by Tuur Vandeputte, Michael Ghijs, Michiel Peeters, Alexander De Man, Daan Van Hauwermeiren, Eduardo Dos Santos Schultz, Tamas Vigh, Fanny Stauffer, Ingmar Nopens and Thomas De Beer
Powders 2023, 2(2), 232-258; https://doi.org/10.3390/powders2020016 - 4 Apr 2023
Cited by 3 | Viewed by 2647
Abstract
In the last decade, twin-screw wet granulation became an essential technology for continuous pharmaceutical tablet production. Consequently, interest in (semi-)continuous fluidized bed drying systems as a subsequent processing unit has grown. In parallel, it has become pivotal to fully understand and control manufacturing [...] Read more.
In the last decade, twin-screw wet granulation became an essential technology for continuous pharmaceutical tablet production. Consequently, interest in (semi-)continuous fluidized bed drying systems as a subsequent processing unit has grown. In parallel, it has become pivotal to fully understand and control manufacturing processes in line with in the quality-by-design paradigm. Formulation-generic prediction models would enormously facilitate digitally enhanced process development and require dedicated experimental data collection and process knowledge. To obtain this knowledge, three experimental campaigns were performed in this work. Firstly, an investigation into the effect of dryer process settings on drying behavior is presented. Secondly, the effect of active pharmaceutical ingredient properties on drying was assessed by producing granules of similar particle size and porosity and evaluating their drying and breakage behavior. Finally, additional experiments with varying active pharmaceutical ingredients and drug load were conducted to increase the genericity of the data set. This knowledge can be used in mathematical process modelling. Full article
(This article belongs to the Special Issue Feature Papers in Powders)
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<p>Schematic representation of the procedure followed to determine the four different sampling times by considering the filling time and bed temperature. To illustrate, this figure shows the bed temperature curve of experiment N9 with a total drying time of 1000 s.</p>
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<p><bold>Observed GSDs for J1F50 experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 8 subplots indicates a change in either LS, T or FT.</p>
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<p><bold>Observed GSDs for J1F50 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 6 subplots indicates a repeated center point experiment at both LS ratios.</p>
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<p><bold>Observed LoD for J1F50 experiments.</bold> The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the total fill level. From left to right, the dry inlet air temperature is increased. While the LS ratio is decreased from top to bottom.</p>
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<p><bold>Measured AoRs across all J1F50 experiments</bold>. Results are compared between the low LS and high LS for air-dried granules, marker color corresponds to the drying times after the filling period. The <italic>x</italic>-axis corresponds with the experimental number as given in <xref ref-type="table" rid="powders-02-00016-t0A2">Table A2</xref>.</p>
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<p><bold>Measured AoRs for the U2SF50, U2D50 and G1R50 experiments</bold> varying the LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>) and fill level (<bold>right</bold>). Marker color corresponds to the formulation type. Both the average and 95% confidence interval are shown for each experiment.</p>
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<p><bold>Measured friability for the U2SF50, U2D50 and G1R50 experiments</bold> varying the LS ratio (left), inlet air temperature (middle) and fill level (right). Marker color corresponds to the formulation type. Both the average and 95% confidence interval are shown for each experiment.</p>
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<p><bold>Observed GSDs for J2F5 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 3 subplots indicates a repeated center point experiment.</p>
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<p><bold>Observed LoD for J2F5 experiments.</bold> The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p>Scatterplot of all preliminary granulation experiments using the first two principal components of the KPCA applied to GSD data. The experiments are colored by formulation type.</p>
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<p>Scatterplot of the MMD between the data points obtained with the same granulation settings but different formulation types: U2D50 VS U2SF50 (<bold>left</bold>), U2SF50 VS G1R50 (<bold>middle</bold>) and U2D50 VS G1R50 (<bold>right</bold>).</p>
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<p><bold>Observed granule size distribution (GSDs) for U1R50 experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 8 subplots indicates a change in ether liquid-to-solid (LS), inlet air temperature or FT.</p>
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<p><bold>Observed GSDs for U1R50 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 6 subplots indicates a repeated center point experiment at both LS ratios.</p>
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<p><bold>Observed GSDs for U2SF50 experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 6 subplots indicates a change in ether LS, T or fill time (FT).</p>
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<p><bold>Observed GSDs for U2SF50 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 3 subplots indicates a repeated center point experiment.</p>
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<p><bold>Observed GSDs for U2D50 experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 6 subplots indicates a change in ether LS, T or FT.</p>
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<p><bold>Observed GSDs for U2D50 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 3 subplots indicates a repeated center point experiment.</p>
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<p><bold>Observed GSDs for G1R50 experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 6 subplots indicates a change in ether LS, T or FT.</p>
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<p><bold>Observed GSDs for G1R50 center point experiments.</bold> The gray curve represents the GSD after granulation or the initial GSD entering the dryer. The other curves were sampled after the fluid bed dryer, the drying time after filling is indicated by color. Each of the 3 subplots indicates a repeated center point experiment.</p>
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<p><bold>Observed LoD for U1R50 experiments.</bold> The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the total fill level, while the column is positive correlated with the inlet air temperature.</p>
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<p><bold>Observed LoD for U2SF50 experiments.</bold> The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p><bold>Observed LoD for U2D50 experiments.</bold> The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p>Observed LoD for G1R50 experiments. The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p>Observed LoD for J1R50 experiments. The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p>Observed LoD for J3R50 experiments. The gray curve represents the initial moisture content after granulation, while the other curves were sampled after the fluid bed dryer. The drying time after the filling period is indicated by color. The markers indicate the varied process setting LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>), total fill level (<bold>right</bold>).</p>
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<p>Measured static cohesive indexs (CIs) across all J1F50 experiments. Results are compared between the low LS and high LS for air-dried granules, dot color corresponds to the drying times after the filling period.</p>
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<p>Measured CIs for the U2SF50, U2D50 and G1R50 experiments varying the LS ratio (<bold>left</bold>), inlet air temperature (<bold>middle</bold>) and fill level (<bold>right</bold>). Dot color corresponds to the formulation type. Both the average and 95% confidence interval are shown for each experiment.</p>
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14 pages, 5866 KiB  
Article
Influence of the Feedstock Preparation on the Properties of Highly Filled Alumina Green-Body and Sintered Parts Produced by Fused Deposition of Ceramic
by Thomas Heim and Frank Kern
Ceramics 2023, 6(1), 241-254; https://doi.org/10.3390/ceramics6010014 - 11 Jan 2023
Cited by 3 | Viewed by 3059
Abstract
This paper investigates new approaches for the blending and plastification of ceramic powder with a binder to form fused deposition of ceramic (FDC) feedstock. The fabrication of highly filled ceramic filaments was accomplished using the granulation by agitation technique, followed by twin-screw extruder [...] Read more.
This paper investigates new approaches for the blending and plastification of ceramic powder with a binder to form fused deposition of ceramic (FDC) feedstock. The fabrication of highly filled ceramic filaments was accomplished using the granulation by agitation technique, followed by twin-screw extruder homogenization and single-screw extruder filament extrusion. The feedstocks are based on alumina (Al2O3) powders, which were prepared with an industrial binder through three different routes: wet granulation, melt granulation and melt granulation with a suspension. After printing cubic samples and tensile test specimens on a commercial fused deposition modelling (FDM) printer, the properties of the resulting green-body and sintered parts were investigated. The green-body mechanical values are compared with results from commercially available filaments. Mixing the binder with the alumina powder and surfactant in a suspension produces the lowest viscosity and the best elongation at break. Full article
(This article belongs to the Special Issue Advances in Ceramics)
Show Figures

Figure 1

Figure 1
<p>Schematic representation of the process.</p>
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<p>Schematic representation of the filament pulling machine. 1: nozzle of the single-screw extruder, 2: filament, 3: water pump, 4: water container, 5: guide wheel, 6: sponge, 7: stepper motor, 8: timing belt transmission, 9: PU rubber conveyor wheel, 10: laser measuring head, 11: filament spool.</p>
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<p>Time–temperature debinding program.</p>
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<p>Geometry and dimensions of 1BA EN ISO 527-2:2012 tensile test specimen <a href="#B19-ceramics-06-00014" class="html-bibr">19</a>.</p>
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<p>Particle size distribution of the raw CT 3000 LS SG alumina powder.</p>
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<p>SEM micrographs of the ground cross-sections of the V1 filament (<b>a</b>), V2 filament (<b>b</b>), V3 filament (<b>c</b>) at mag. ×45, and V3 printed cubic sample (<b>d</b>) at mag. ×500, Z: vertical printing direction.</p>
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<p>Young’s moduli (<b>a</b>), ultimate tensile strength (<b>b</b>), elongation at break (<b>c</b>) of the V1, V2, V3, Si (SiCeram), Ze (Zetamix) printed green-body tensile specimens.</p>
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<p>Complex viscosity of the V1, V2, V3, SiCeram and Zetamix filaments at 145 °C.</p>
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<p>Sintering shrinkage of the V1, V2 and V3 printed cubic samples.</p>
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<p>Apparent porosity (<b>a</b>), and relative bulk density (<b>b</b>) of the V1, V2, V3 sintered samples at 1550 °C for 120 min.</p>
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<p>Indentation modulus (<b>a</b>), Vickers hardness HV10 (<b>b</b>), indentation toughness after Niihara (<b>c</b>).</p>
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<p>SEM micrographs of the cross-section of a V3 sample after sintering at 1550 °C for 120 min and thermal etching at 1300 °C for 10 min. at mag. ×500 (<b>a</b>) and mag. ×2000 (<b>b</b>), Z: vertical printing direction.</p>
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