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控制三种不同的连续制药工艺:软传感器的应用。

Control of three different continuous pharmaceutical manufacturing processes: Use of soft sensors.

机构信息

Research Center Pharmaceutical Engineering, 8010 Graz, Austria; European Consortium on Continuous Pharmaceutical Manufacturing (ECCPM), 8010 Graz, Austria.

University of Eastern Finland, School of Pharmacy, PROMIS-Centre, FI-70211 Kuopio, Finland; European Consortium on Continuous Pharmaceutical Manufacturing (ECCPM), 8010 Graz, Austria.

出版信息

Int J Pharm. 2018 May 30;543(1-2):60-72. doi: 10.1016/j.ijpharm.2018.03.027. Epub 2018 Mar 16.

Abstract

One major advantage of continuous pharmaceutical manufacturing over traditional batch manufacturing is the possibility of enhanced in-process control, reducing out-of-specification and waste material by appropriate discharge strategies. The decision on material discharge can be based on the measurement of active pharmaceutical ingredient (API) concentration at specific locations in the production line via process analytic technology (PAT), e.g. near-infrared (NIR) spectrometers. The implementation of the PAT instruments is associated with monetary investment and the long term operation requires techniques avoiding sensor drifts. Therefore, our paper proposes a soft sensor approach for predicting the API concentration from the feeder data. In addition, this information can be used to detect sensor drift, or serve as a replacement/supplement of specific PAT equipment. The paper presents the experimental determination of the residence time distribution of selected unit operations in three different continuous processing lines (hot melt extrusion, direct compaction, wet granulation). The mathematical models describing the soft sensor are developed and parameterized. Finally, the suggested soft sensor approach is validated on the three mentioned, different continuous processing lines, demonstrating its versatility.

摘要

连续制药生产相对于传统的批量生产的一个主要优势是可以增强过程控制,通过适当的排放策略减少不合格品和废料。材料排放的决策可以基于通过过程分析技术(PAT)在生产线的特定位置测量活性药物成分(API)的浓度来做出,例如近红外(NIR)光谱仪。PAT 仪器的实施需要货币投资,并且长期运行需要避免传感器漂移的技术。因此,我们的论文提出了一种从给料器数据预测 API 浓度的软传感器方法。此外,该信息可用于检测传感器漂移,或作为特定 PAT 设备的替代/补充。本文通过实验确定了三个不同连续处理线(热熔挤出、直接压片、湿法制粒)中选定单元操作的停留时间分布。开发并参数化了描述软传感器的数学模型。最后,在上述三个不同的连续处理线上验证了所提出的软传感器方法,证明了其通用性。

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