对于拉曼模型校准的合成光谱库
Louis V Hellequin1,2, Vicent J Borràs1, Patrick Romann3
1University of Applied Sciences Northwestern Switzerland FHNW, Muttenz, Switzerland.
Analytical and bioanalytical chemistry
|July 8, 2025
概括
这项研究引入了in silico spiking,以创建用于拉曼光谱的合成光谱库. 这种新的方法大大降低了构建生物过程预测模型的时间和成本.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 生物技术是生物技术.
背景情况:
- 拉曼光谱对于生物处理中的过程分析技术 (PAT) 有价值.
- 对于拉曼光谱的模型构建目前是耗时且昂贵的.
研究的目的:
- 探索使用in silico spiking来创建合成光谱库 (SSL).
- 为了减少与拉曼光谱模型构建相关的成本和时间.
主要方法:
- 开发了一个快速校准工作流程,使用与水混合的物理纯化合物.
- 用于各种分析物的纯光谱指纹的化.
- 通过融合哺乳动物细胞培养谱,矩阵可变性和纯成分谱,创建了一个SSL.
主要成果:
- 在in silico spiking生成的光谱数据与物理spiking可比.
- 该SSL方法有效地减少了模型构建成本和时间.
- 创建了一个丰富的信息丰富的光谱图书馆.
结论:
- In silico spiking 是一种可行且高效的方法来增强拉曼校准.
- 这种方法为生物过程监测中的回归算法提供了坚实的基础.
- 合成光谱库方法显著改善了拉曼光谱模型开发.
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