通过多变量数据分析,探索LC-MS多属性方法与传统染色学产品质量检测之间的相关性.
Tingting Jiang1, Francis Kwofie1, Nick Attanasio1
1Global Vaccines and Biologics Commercialization, Merck & Co., Inc., 770 Sumneytown Pike, West Point, Pennsylvania, 19486, USA.
The AAPS journal
|November 21, 2024
概括
开发了一种用于生物治疗的快速多属性方法 (MAM) 工作流. 该方法使用质谱学量化预测传统的质量属性,增强过程理解和评估质量控制释放的MAM.
科学领域:
- 生物制药学分析
- 分析化学 分析化学
- 过程分析技术 (PAT) 是一种分析技术.
背景情况:
- 生物治疗药物由于复杂的制造过程而表现出异质性.
- 对关键质量属性 (CQA) 的监测对于安全性和有效性至关重要.
- 基于质谱 (MS) 的多属性方法 (MAM) 是有希望的,但需要对传统方法进行验证.
研究的目的:
- 为CQA监控开发一个简单,稳健和快速的MAM工作流.
- 建立一个全面的数据库,将MAM与传统分析方法相关联.
- 评估MAM作为替代传统质量控制试验的适用性.
主要方法:
- 为生物治疗性CQAs开发一个快速的MAM工作流程.
- 创建一个数据库 (约700个样本),包含MAM,电荷变异和氧化数据.
- 应用多变量数据分析 (MVDA),包括部分最小平方回归 (PLSR),以将MAM数据与传统测试相关联.
主要成果:
- 成功创建了一个集成MAM和传统分析数据的数据库.
- 通过PLSR模型使用MAM数据,证明了电荷变异 (离子交换染色学 - IEX) 和氧化水平 (疏水相互作用染色学 - HIC) 的定量预测.
- 强调了MAM和传统产品质量测试之间的强有力的相互联系.
结论:
- 快速的MAM工作流程使生物治疗CQA的可靠监控成为可能.
- MVDA有效地利用MAM数据来预测传统测试的结果,支持过程理解.
- 研究结果支持评估MAM作为传统释放试验的潜在替代品,增强生物制药质量控制.
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