The stability of biopharmaceutical therapeutics over the storage period/shelf life has been a challenging concern for manufacturers. A noble strategy for mapping best and suitable storage conditions for recombinant human serum albumin (rHSA) in laboratory mixture was optimized using chromatographic data as per principal component analysis (PCA), and similarity was defined using hierarchical cluster analysis. In contrast, separability was defined using linear discriminant analysis (LDA) models. The quantitation was performed for rHSA peak (analyte of interest) and its degraded products, i.e., dimer, trimer, agglomerates and other degradation products. The chromatographic variables were calculated using validated stability-indicating assay method. The chromatographic data mapping was done for the above-mentioned peaks over three months at different temperatures, i.e., 20°C, 5–8°C and at room temperature (25°C). The PCA had figured out the ungrouped variable, whereas supervised mapping was done using LDA. As an outcome result of LDA, about 60% of data were correctly classified with the highest sensitivity for 25°C (Aq), 25°C and 5–8°C (Aq with 5% glucose as a stabilizer), whereas the highest specificity was observed for samples stored at 5–8°C (Aq with 5% glucose as a stabilizer).

中文翻译：

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监督和非监督学习方法在绘制生物制药产品储存条件中的应用——以人血清白蛋白为例

生物制药疗法在储存期/保质期内的稳定性一直是制造商面临的一个具有挑战性的问题。根据主成分分析 (PCA) 使用色谱数据优化了绘制实验室混合物中重组人血清白蛋白 (rHSA) 最佳和合适储存条件的高贵策略，并使用层次聚类分析定义了相似性。相反，可分离性是使用线性判别分析 (LDA) 模型定义的。对 rHSA 峰（感兴趣的分析物）及其降解产物（即二聚体、三聚体、附聚物和其他降解产物）进行定量。使用经过验证的稳定性指示测定方法计算色谱变量。在不同温度下，即 20°C、5–8°C 和室温 (25°C) 下，对上述峰进行了三个月的色谱数据映射。PCA 计算出未分组的变量，而监督映射是使用 LDA 完成的。作为 LDA 的结果，大约 60% 的数据被正确分类，对 25°C (Aq)、25°C 和 5–8°C（Aq，含 5% 葡萄糖作为稳定剂）具有最高灵敏度，而最高灵敏度对于储存在 5–8°C 的样品（含有 5% 葡萄糖作为稳定剂的 Aq）观察到特异性。