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用于药物固体剂型连续制造中助流剂和润滑剂效应的机理降阶模型(ROMs)的开发。

Development of mechanistic reduced order models (ROMs)for glidant and lubricant effects in continuous manufacturing of pharmaceutical solid-dosage forms.

作者信息

Bachawala Sunidhi, Gonzalez Marcial

机构信息

School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.

Ray W. Herrick Laboratories, Purdue University, West Lafayette, IN 47907, USA.

出版信息

ESCAPE. 2022;51:1129-1134. doi: 10.1016/b978-0-323-95879-0.50189-2.

Abstract

As the pharmaceutical industry transitions from batch to continuous manufacturing, real-time monitoring, and mechanistic model-based control are essential to conform to FDA quality standards. Glidants and lubricants are known to affect the Critical Quality Attributes (CQAs) of a tablet such as tensile strength, tablet porosity, and dissolution profile (Razavi et al., 2018; Apeji and Olowosulu, 2020). Quantitative models for predicting these effects are essential for enabling centralized control strategies of lubricant and glidant feeding and blending in direct compression tableting lines. This work presents the development of mechanistic reduced order models to capture the effects of lubricant (magnesium stearate) and glidant (silica) on CQAs and Critical Process Parameters (CPPs). A Latin Hypercube experimental campaign with thirty different mixing conditions of silica with MCC (Avicel PH200) and APAP (Acetaminophen) was carried out using a Natoli NP400 tablet press and a SOTAX AT4 tablet tester. Experiments show that the tensile strength and blend bulk density are significantly affected by the mixing conditions of silica. Similarly, adding magnesium stearate (MgSt) changes the bulk density of the blend, compaction force required to form a tablet, and tensile strength of the tablet, depending on the lubrication conditions (Mehrotra et al., 2007; Razavi et al., 2018).

摘要

随着制药行业从间歇生产向连续生产转型,实时监测和基于机理模型的控制对于符合FDA质量标准至关重要。已知助流剂和润滑剂会影响片剂的关键质量属性(CQAs),如拉伸强度、片剂孔隙率和溶出曲线(拉扎维等人,2018年;阿佩吉和奥洛沃苏卢,2020年)。预测这些影响的定量模型对于在直接压片生产线中实现润滑剂和助流剂进料及混合的集中控制策略至关重要。这项工作展示了机理降阶模型的开发,以捕捉润滑剂(硬脂酸镁)和助流剂(二氧化硅)对CQAs和关键工艺参数(CPPs)的影响。使用纳托利NP400压片机和SOTAX AT4片剂测试仪,开展了一项拉丁超立方实验活动,涉及二氧化硅与微晶纤维素(阿维森纳PH200)和对乙酰氨基酚(扑热息痛)的三十种不同混合条件。实验表明,二氧化硅的混合条件对拉伸强度和混合堆密度有显著影响。同样,添加硬脂酸镁(MgSt)会改变混合物的堆密度、压片所需的压力以及片剂的拉伸强度,这取决于润滑条件(梅赫罗特拉等人,2007年;拉扎维等人,2018年)。

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