Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, Ghent 9000, Oost-Vlaanderen, Belgium.
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.
Int J Pharm. 2023 Oct 15;645:123391. doi: 10.1016/j.ijpharm.2023.123391. Epub 2023 Sep 9.
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.
双螺杆湿法造粒（TSWG）作为一种有前途的连续替代传统间歇流化床和高剪切湿法造粒技术的方法，备受关注。尽管具有潜力，但原材料性质对 TSWG 可加工性的影响仍未得到充分探索。此外，缺乏针对具有新活性药物成分（API）的 TSWG 工艺开发的支持模型，这也增加了挑战。本研究通过引入四个偏最小二乘（PLS）模型来解决这些差距，这些模型基于初始材料特性，分别近似于适用的液固比（L/S）范围和所得颗粒特性（即颗粒大小和脆性）。前两个 PLS 模型分别将 TSWG 的最低和最高适用 L/S 比与配方混合物特性联系起来。第三个和第四个 PLS 模型分别根据起始 API 特性和双螺杆湿法造粒的应用 L/S 比预测颗粒大小和脆性。通过分析所开发的 PLS 模型，发现与水相关的材料特性（例如，溶解度、润湿性、溶解速率）以及密度和流动相关特性（例如，流动函数系数）会影响 TSWG 的可加工性。此外，通过使用这些模型为三种新的 API 和相关配方提出合适的 L/S 比范围（即得到具有所需特性的颗粒），并对其进行实验验证，评估了所开发的 PLS 模型的适用性。总体而言，本研究有助于更好地理解原材料性质对 TSWG 可加工性的影响。此外，所开发的 PLS 模型可用于为新 API 提出合适的 TSWG 工艺参数，从而减少工艺开发过程中的实验工作量。
