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三种流式影像显微镜仪器在评估生物制药中四种类型亚可见颗粒的图像分析中的应用。

Utility of Three Flow Imaging Microscopy Instruments for Image Analysis in Evaluating four Types of Subvisible Particle in Biopharmaceuticals.

机构信息

Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan.

Department of Pharmacy; Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-Universitaet Muenchen, Munich, Germany.

出版信息

J Pharm Sci. 2022 Nov;111(11):3017-3028. doi: 10.1016/j.xphs.2022.08.006. Epub 2022 Aug 7.

Abstract

Subvisible particles (SVPs) are a critical quality attribute of parenteral and ophthalmic products. United States Pharmacopeia recommends the characterizations of SVPs which are classified into intrinsic, extrinsic, and inherent particles. Flow imaging microscopy (FIM) is useful as an orthogonal method in both the quantification and classification of SVPs because FIM instruments provide particle images. In addition to the conventionally used FlowCam (Yokogawa Fluid Imaging Technologies) and Micro-Flow Imaging (Bio-Techne) instruments, the iSpect DIA-10 (Shimadzu) instrument has recently been released. The three instruments have similar detection principles but different optical settings and image processing, which may lead to different results of the quantification and classification of SVPs based on the information from particle images. The present study compares four types of SVP (protein aggregates, silicone oil droplets, and surrogates for solid free-fatty-acid particles, milled-lipid particles, and sprayed-lipid particles) to compare the results of size distributions and classification abilities obtained using morphological features and a deep-learning approach. Although the three FIM instruments were effective in classifying the four types of SVP through convolutional neural network analysis, there was no agreement on the size distribution for the same protein aggregate solution, suggesting that using the classifiers of the FIM instruments could result in different evaluations of SVPs in the field of biopharmaceuticals.

摘要

亚可见颗粒 (SVPs) 是注射剂和眼用制剂的关键质量属性。美国药典推荐对 SVPs 进行特性描述,SVPs 可分为固有、外在和固有颗粒。流影像显微镜 (FIM) 是一种有用的正交方法,可用于 SVPs 的定量和分类,因为 FIM 仪器可提供颗粒图像。除了常规使用的 FlowCam(横河流体成像技术)和 Micro-Flow Imaging(百泰克)仪器外,最近还推出了 iSpect DIA-10(岛津)仪器。这三种仪器具有相似的检测原理,但光学设置和图像处理不同,这可能导致基于颗粒图像信息的 SVPs 定量和分类结果不同。本研究比较了四种类型的 SVP(蛋白质聚集体、硅油滴、固体无脂酸颗粒的替代物、粉碎脂质颗粒和喷雾脂质颗粒),以比较使用形态特征和深度学习方法获得的大小分布和分类能力的结果。尽管三种 FIM 仪器通过卷积神经网络分析有效地对四种类型的 SVP 进行了分类,但对于相同的蛋白质聚集溶液,它们在大小分布上没有一致性,这表明使用 FIM 仪器的分类器可能会导致生物制药领域对 SVPs 的不同评估。

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