Identification of therapeutic allergen products using their Raman spectral fingerprint

IF 3.7 2区化学 Q2 AUTOMATION & CONTROL SYSTEMS

Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-02-14 DOI:10.1016/j.chemolab.2025.105340

Christian Ickes , Pirya Rani , Kristiyana Tsenova , Johanna Echternach , Frank Führer , Detlef Bartel , Christel Kamp

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Abstract

Raman spectroscopy is a widely used technique for the identification of chemical substances and in the quality control of pharmaceutical products. Inelastic scattering of laser light generates unique fingerprints of chemical substances which allows for identification of products and quantification of active components. Using this non-destructive technique for biomedicines like vaccines or therapeutic allergen products introduces new challenges in terms of experimental setup, spectral processing, and their standardization. We explore experimental setups and use machine learning techniques to evaluate the potential of Raman spectroscopy to distinguish between therapeutic allergen products from different manufacturers with closely related bee and wasp venoms as Active Pharmaceutical Ingredients (APIs). A comparison of various models shows that a differentiation of products is possible based on their Raman spectra at accuracies above 95%. A deeper analysis allows to identify key regions in the spectra for differentiation. These can guide further research towards the identification and quantification of biochemical compounds of interest. In conclusion, this proof-of-concept study shows the applicability of Raman spectroscopy in the quality assurance of biomedicines and suggests directions for further in-depth analyses.

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利用拉曼光谱指纹图谱鉴别治疗性过敏原产品

拉曼光谱是一种广泛应用于化学物质鉴定和药品质量控制的技术。激光的非弹性散射产生化学物质的独特指纹，允许产品的识别和有效成分的量化。在疫苗或治疗性过敏原产品等生物医药中使用这种非破坏性技术，在实验设置、光谱处理及其标准化方面带来了新的挑战。我们探索实验设置并使用机器学习技术来评估拉曼光谱的潜力，以区分来自不同制造商的治疗性过敏原产品，这些产品具有密切相关的蜜蜂和黄蜂毒液作为活性药物成分（api）。各种模型的比较表明，基于拉曼光谱的产品区分是可能的，精度在95%以上。更深入的分析可以识别光谱中的关键区域以进行区分。这些可以指导对感兴趣的生化化合物的鉴定和定量的进一步研究。总之，这项概念验证研究表明了拉曼光谱在生物医学质量保证中的适用性，并为进一步深入分析提供了方向。

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来源期刊

Chemometrics and Intelligent Laboratory Systems 工程技术-分析化学

CiteScore

7.50

自引率

7.70%

发文量

169

审稿时长

3.4 months

期刊介绍： Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.