class='kwd-title'>Keywords: Fluid bed granulatio'/> Industrial application of heat- and mass balance model for fluid-bed granulation for technology transfer and design space exploration
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Industrial application of heat- and mass balance model for fluid-bed granulation for technology transfer and design space exploration

机译:流化床制粒热质平衡模型在工业中的技术应用及设计空间探索

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摘要

class="kwd-title">Keywords: Fluid bed granulation, Technology transfer, Industrial application, Heat- and mass balances, Mechanistic modeling, Digital twin class="head no_bottom_margin" id="ab010title">AbstractThis work demonstrates the application of state-of-the-art modeling techniques in pharmaceutical manufacturing for fluid bed granulation at varying scales to successfully predict process conditions and ultimately replace experiments during a technology transfer of five products. We describe a mathematical model able to simulate the time-dependent moisture profile in a fluid bed granulation process. The applicability of this model is then demonstrated by calibrating and validating it over a range of operating conditions, manufacturing scales, and formulations. The inherent capability of the moisture profile to serve as a simple, scale-independent surrogate is shown by the large number of successful scale-ups and transfers. A methodology to use this ‘digital twin’ to systematically explore the effects of uncertainty inherent in the process input and model parameter spaces and their impact on the process outputs is described. Two case studies exemplifying the utilization of the model in industrial practice to assess process robustness are provided. Lastly, a pathway to leverage model results to establish proven acceptable ranges for individual parameters is outlined.
机译:<!-fig ft0-> <!-fig @ position =“ position” anchor“ == f4-> <!-fig mode =” anchred“ f5-> <!-fig / graphic | fig / alternatives / graphic mode =“ anchored” m1-> class =“ kwd-title”>关键字:流化床制粒,技术转让,工业应用,热量和质量平衡,机械模型,数字孪生 class =“ head no_bottom_margin” id =“ ab010title”>摘要该工作演示了最新模型技术在不同规模的流化床造粒药物制造中的应用,以成功预测工艺条件和最终在五种产品的技术转让过程中取代了实验。我们描述了一种数学模型,该模型能够模拟流化床制粒过程中随时间变化的湿度曲线。然后,通过在一系列操作条件,制造规模和配方下进行校准和验证来证明该模型的适用性。大量成功的按比例放大和转移显示了水分曲线作为简单的,与尺度无关的替代物的固有能力。描述了一种使用“数字孪生”系统地探索过程输入和模型参数空间中固有的不确定性的影响及其对过程输出的影响的方法。提供了两个案例研究,以举例说明该模型在工业实践中的使用,以评估过程的鲁棒性。最后,概述了利用模型结果为各个参数建立公认的可接受范围的途径。

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