少是多:对生物过程监测中的拉曼光谱的多变量回归模型的实用见解
Antoine Borg1,2,3, Mourad Elhabiri2, Stéphane Le Calvé3
1Euroapi, France.
Biotechnology and bioengineering
|December 20, 2025
概括
这一审查简化了生物处理中的过程分析技术 (PAT) 的化学计量. 它提供实用的拉曼光谱法,用于稳健的实时葡萄糖和乳酸监测,使PAT更容易获得.
科学领域:
- 生物技术是生物技术.
- 分析化学 分析化学
- 工艺工程是过程工程.
背景情况:
- 过程分析技术 (PAT) 对于实时生物过程监测至关重要,但面临着有限的采用.
- 化学测量和供应商沟通的复杂性阻碍了PAT的实施,特别是在定量在线监测方面.
研究的目的:
- 为了消除生物处理中的基于拉曼光谱的多变量回归模型的化学测量.
- 为开发可靠和可维护的PAT模型提供简化,实用的工作流程.
- 挑战化学测量是生物工艺应用无法使用的概念.
主要方法:
- 化学测量模型开发的批判性评估工作流程:预处理,预处理,建模和评估.
- 专注于拉曼光谱法用于多变量回归分析.
- 关于发酵中的葡萄糖监测和细胞培养中的乳酸盐监测的案例研究.
主要成果:
- 展示了开发基于拉曼光谱的化学测量模型的实际工作流程.
- 突出了模型开发和应用中的常见陷和最佳实践.
- 展示了在实时血糖和乳酸监测中的成功应用.
结论:
- 化学测量可以简化,以便在生物处理中实际实施PAT.
- 通过简化方法,可以实现强大,透明和可维护的模型.
- 研究人员可以使用拉曼光谱来开发准确和可靠的模型来监测现实世界中的生物过程.
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