Characterizing Silicone Oil-Induced Protein Aggregation with Stimulated Raman Scattering Imaging
Characterizing Silicone Oil-Induced Protein Aggregation with Stimulated Raman Scattering Imaging
复制标题
用受激拉曼散射成像表征硅油诱导的蛋白质聚集
DOI：
10.1021/acs.molpharmaceut.3c00391
复制
发表时间：
2023
影响因子：
4.9
通讯作者：
Fu, Dan
中科院分区：
文献类型：
--
作者：
Wong, Brian;Zhao, Xi;Su, Yongchao;Ouyang, Hanlin;Rhodes, Timothy;Xu, Wei;Xi, Hanmi;Fu, Dan
生物制药产品中的颗粒由于对产品质量和安全性产生不利影响而存在高风险。药品中颗粒的识别和定量对于了解颗粒形成机制非常重要，这有助于在制剂开发和制造过程中制定颗粒形成的控制策略。然而，现有的分析技术（例如微流成像和光阻测量）缺乏检测小于 2 μm 颗粒的灵敏度和分辨率。更重要的是，这些技术无法提供化学信息来确定颗粒成分。在这项工作中，我们通过应用受激拉曼散射（SRS）显微镜技术来监测预填充注射器筒中形成的蛋白质颗粒和硅油滴的C-H拉曼拉伸模式，克服了这些挑战。通过比较各组分的相对信号强度和光谱特征，大多数颗粒可归类为蛋白质-硅油聚集体。我们进一步表明，形态特征并不能很好地反映颗粒组成。我们的方法能够以无标记的方式利用化学和空间信息来量化蛋白质治疗中的聚集，从而有可能实现高通量筛选或聚集机制的研究。
Particles in biopharmaceutical products present high risks due to their detrimental impacts on product quality and safety. Identification and quantification of particles in drug products are important to understand particle formation mechanisms, which can help develop control strategies for particle formation during the formulation development and manufacturing process. However, existing analytical techniques such as microflow imaging and light obscuration measurement lack the sensitivity and resolution to detect particles with sizes smaller than 2 μm. More importantly, these techniques are not able to provide chemical information to determine particle composition. In this work, we overcome these challenges by applying the stimulated Raman scattering (SRS) microscopy technique to monitor the C–H Raman stretching modes of the proteinaceous particles and silicone oil droplets formed in the prefilled syringe barrel. By comparing the relative signal intensity and spectral features of each component, most particles can be classified as protein–silicone oil aggregates. We further show that morphological features are poor indicators of particle composition. Our method has the capability to quantify aggregation in protein therapeutics with chemical and spatial information in a label-free manner, potentially allowing high throughput screening or investigation of aggregation mechanisms.