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Subvisible Particle Content, Formulation, and Dose of an Erythropoietin Peptide Mimetic Product Are Associated With Severe Adverse Postmarketing Events.一种促红细胞生成素肽模拟产品的亚可见颗粒含量、制剂和剂量与严重的上市后不良事件相关。
J Pharm Sci. 2016 Mar;105(3):1023-7. doi: 10.1016/S0022-3549(15)00180-X. Epub 2016 Feb 3.
2
The Use of Index-Matched Beads in Optical Particle Counters.光学粒子计数器中指数匹配珠的应用。
J Res Natl Inst Stand Technol. 2014 Jan 8;119:674-82. doi: 10.6028/jres.119.029. eCollection 2014.
3
Correcting the Relative Bias of Light Obscuration and Flow Imaging Particle Counters.校正光散射和流动成像粒子计数器的相对偏差。
Pharm Res. 2016 Mar;33(3):653-72. doi: 10.1007/s11095-015-1817-9. Epub 2015 Nov 10.
4
Subvisible (2-100 μm) particle analysis during biotherapeutic drug product development: Part 2, experience with the application of subvisible particle analysis.生物治疗药物产品研发过程中的亚可见(2 - 100微米)颗粒分析:第2部分,亚可见颗粒分析应用经验
Biologicals. 2015 Nov;43(6):457-73. doi: 10.1016/j.biologicals.2015.07.011. Epub 2015 Aug 29.
5
Advanced methods of microscope control using μManager software.使用μManager软件的高级显微镜控制方法。
J Biol Methods. 2014;1(2). doi: 10.14440/jbm.2014.36.
6
Particle shape effects on subvisible particle sizing measurements.颗粒形状对亚可见颗粒尺寸测量的影响。
J Pharm Sci. 2015 Mar;104(3):971-87. doi: 10.1002/jps.24263. Epub 2014 Dec 1.
7
An interlaboratory comparison of sizing and counting of subvisible particles mimicking protein aggregates.模拟蛋白质聚集体的亚可见颗粒大小测定与计数的实验室间比对
J Pharm Sci. 2015 Feb;104(2):666-77. doi: 10.1002/jps.24287. Epub 2014 Nov 24.
8
Unmasking translucent protein particles by improved micro-flow imaging™ algorithms.通过改进的微流成像™算法揭示半透明蛋白质颗粒。
J Pharm Sci. 2014 Jan;103(1):107-14. doi: 10.1002/jps.23786. Epub 2013 Nov 26.
9
Flow imaging microscopy for protein particle analysis--a comparative evaluation of four different analytical instruments.流场成像显微镜用于蛋白质颗粒分析——四种不同分析仪器的比较评估。
AAPS J. 2013 Oct;15(4):1200-11. doi: 10.1208/s12248-013-9522-2. Epub 2013 Aug 31.
10
How subvisible particles become invisible-relevance of the refractive index for protein particle analysis.亚可见颗粒如何变得不可见——折射率在蛋白质颗粒分析中的相关性。
J Pharm Sci. 2013 May;102(5):1434-46. doi: 10.1002/jps.23479. Epub 2013 Mar 5.

用于确定成像亚可见颗粒边界的可变阈值法

Variable Threshold Method for Determining the Boundaries of Imaged Subvisible Particles.

作者信息

Cavicchi Richard E, Collett Cayla, Telikepalli Srivalli, Hu Zhishang, Carrier Michael, Ripple Dean C

机构信息

Bioprocess Measurements Group, National Institute of Standards and Technology, Gaithersburg, Maryland 20899.

West Virginia Wesleyan College, Buckhannon, West Virginia 26201.

出版信息

J Pharm Sci. 2017 Jun;106(6):1499-1507. doi: 10.1016/j.xphs.2017.02.005. Epub 2017 Feb 15.

DOI:10.1016/j.xphs.2017.02.005
PMID:28209364
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5535275/
Abstract

An accurate assessment of particle characteristics and concentrations in pharmaceutical products by flow imaging requires accurate particle sizing and morphological analysis. Analysis of images begins with the definition of particle boundaries. Commonly a single threshold defines the level for a pixel in the image to be included in the detection of particles, but depending on the threshold level, this results in either missing translucent particles or oversizing of less transparent particles due to the halos and gradients in intensity near the particle boundaries. We have developed an imaging analysis algorithm that sets the threshold for a particle based on the maximum gray value of the particle. We show that this results in tighter boundaries for particles with high contrast, while conserving the number of highly translucent particles detected. The method is implemented as a plugin for FIJI, an open-source image analysis software. The method is tested for calibration beads in water and glycerol/water solutions, a suspension of microfabricated rods, and stir-stressed aggregates made from IgG. The result is that appropriate thresholds are automatically set for solutions with a range of particle properties, and that improved boundaries will allow for more accurate sizing results and potentially improved particle classification studies.

摘要

通过流动成像准确评估药品中的颗粒特性和浓度需要准确的颗粒尺寸测量和形态分析。图像分析始于颗粒边界的定义。通常,单个阈值定义了图像中像素被纳入颗粒检测的水平,但根据阈值水平,这会导致要么遗漏半透明颗粒,要么由于颗粒边界附近强度的光晕和梯度而使透明度较低的颗粒尺寸过大。我们开发了一种成像分析算法,该算法基于颗粒的最大灰度值为颗粒设置阈值。我们表明,这会为高对比度颗粒产生更紧密的边界,同时保留检测到的高度半透明颗粒的数量。该方法作为开源图像分析软件FIJI的插件实现。该方法针对水中和甘油/水溶液中的校准珠、微制造棒的悬浮液以及由IgG制成的搅拌应力聚集体进行了测试。结果是,对于具有一系列颗粒特性的溶液会自动设置合适的阈值,并且改进的边界将允许获得更准确的尺寸测量结果,并可能改善颗粒分类研究。