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Exploring the effect of raw material properties on continuous twin-screw wet granulation manufacturability

易碎性 造粒 颗粒(地质) 原材料 材料科学 流动特性 工艺工程 溶解 数学 复合材料 化学 化学工程 机械 工程类 有机化学 物理 聚合物 乙基纤维素
作者
Michiel Peeters,Ana Alejandra Barrera Jiménez,Kensaku Matsunami,Daan Van Hauwermeiren,F. J. Stauffer,Lærke Arnfast,Tamás Vígh,Ingmar Nopens,Thomas De Beer
出处
期刊:International Journal of Pharmaceutics [Elsevier]
卷期号:645: 123391-123391 被引量:3
标识
DOI:10.1016/j.ijpharm.2023.123391
摘要

Twin-screw wet granulation (TSWG) stands out as a promising continuous alternative to conventional batch fluid bed- and high shear wet granulation techniques. Despite its potential, the impact of raw material properties on TSWG processability remains inadequately explored. Furthermore, the absence of supportive models for TSWG process development with new active pharmaceutical ingredients (APIs) adds to the challenge. This study tackles these gaps by introducing four partial least squares (PLS) models that approximate both the applicable liquid-to-solid (L/S) ratio range and resulting granule attributes (i.e., granule size and friability) based on initial material properties. The first two PLS models link the lowest and highest applicable L/S ratio for TSWG, respectively, with the formulation blend properties. The third and fourth PLS models predict the granule size and friability, respectively, from the starting API properties and applied L/S ratio for twin-screw wet granulation. By analysing the developed PLS models, water-related material properties (e.g., solubility, wettability, dissolution rate), as well as density and flow-related properties (e.g., flow function coefficient), were found to be impacting the TSWG processability. In addition, the applicability of the developed PLS models was evaluated by using them to propose suitable L/S ratio ranges (i.e., resulting in granules with the desired properties) for three new APIs and related formulations followed by an experimental validation thereof. Overall, this study helped to better understand the effect of raw material properties upon TSWG processability. Moreover, the developed PLS models can be used to propose suitable TSWG process settings for new APIs and hence reduce the experimental effort during process development.

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