筛选振动光谱技术同时定量粉末混合物中维生素 B1、B6 和 B12 的能力

IF 2.7 3区 化学 Q2 CHEMISTRY, ANALYTICAL
Apostol Todorovski , Nikola Geskovski , Marina Petreska , Eric Deconinck , Hervé Rebière , Natalija Nakov , Katerina Brezovska , Jelena Acevska
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引用次数: 0

摘要

振动光谱技术与多变量建模技术的结合,使这些成熟的分析技术得以广泛应用,并易于进行快速、无损的分析。由于在样品制备过程中不需要使用有害溶剂或试剂,傅立叶变换红外光谱、近红外光谱和拉曼光谱属于环保型技术,被称为 "绿色分析技术"。本研究旨在使用偏最小二乘法(PLS)回归模型,评估 ATR-傅立叶变换红外光谱、近红外光谱和拉曼光谱作为定量粉末混合物中维生素 B1(硫胺素)、B6(吡哆醇)和 B12(氰钴胺)的 PAT 的潜力,并监测粉末混合物的均匀性。将每种振动光谱技术得出的结果与高效液相色谱法得出的结果进行了比较,后者是使用多元分析对复杂基质中的活性物质进行定量的参考分析技术。对所建立的 PLS 模型进行了评估,以确定其对混合粉末中每种活性物质的定量能力。模型的统计指标(解释率(R2X 和 R2Y)、预测能力(Q2 和 RMSEP)和准确度(RMSEE))表明,这些模型适用于混合物粉末中维生素 B1、B6 和 B12 含量的过程估算。B12 含量的估算更具挑战性,这可能是由于其在混合粉末中的含量较低造成的取样问题。尽管如此,观察到的模型变化与 HPLC 得出的结果变化一致,表明混合物缺乏均匀性。因此,可以考虑将定量模型进一步升级为 PAT,用于在维生素混合物生产过程中监测粉末混合物的均匀性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Screening the capability of vibrational spectroscopic techniques for simultaneous quantification of vitamins B1, B6, and B12 in a powder blend

The rising possibilities of vibrational spectroscopy coupled with multivariate modeling, enables many applications of these well-established analytical techniques, easy-to-use for rapid and non-destructive analysis. Owing to the lack of need for hazardous solvents or reagents in sample preparation, FTIR, NIR and Raman spectroscopy belong to the group of environmentally friendly techniques, known as “green analytical techniques”. Such characteristics re-introduce them into the pharmaceutical industry, especially as part of process-analytical-technology (PAT) tools for both qualitative and quantitative analysis.

This research aimed to assess the potential of ATR-FTIR, NIR and Raman as a PAT for the quantification of Vitamins B1 (thiamine), B6 (pyridoxine) and B12 (cyanocobalamin) in a powder blend, using a partial least square (PLS) regression model, as well as to monitor the powder blend homogeneity.

Results from each of the vibrational spectroscopy techniques were compared with those obtained by HPLC, which served as the reference analytical technique for quantifying the active substances in complex matrices using multivariate analysis. The developed PLS models were evaluated for their ability to quantify each of the active substances in the powder blend. The ATR-FTIR, NIR and Raman spectrum segments, revealed by the Variable Importance for Projection (VIP) plot for each model, respectively, were linked to the band assignment of each active ingredient.

The statistical indicators of the models (interpretation rate (R2X and R2Y), predictive ability (Q2 and RMSEP) and accuracy (RMSEE)) demonstrated their suitability for in-process estimation of vitamin B1, B6 and B12 contents in powder blends. Estimating B12 content proved more challenging, likely due to sampling issues related to its low content in the powder blend. Nevertheless, the observed variability in the models aligns with the variability in results obtained by HPLC, indicating the lack of blend homogeneity. Therefore, the quantification models could be considered for a further upgrade as PAT for monitoring the powder blend homogeneity during the manufacturing of vitamin blends.

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来源期刊
Vibrational Spectroscopy
Vibrational Spectroscopy 化学-分析化学
CiteScore
4.70
自引率
4.00%
发文量
103
审稿时长
52 days
期刊介绍: Vibrational Spectroscopy provides a vehicle for the publication of original research that focuses on vibrational spectroscopy. This covers infrared, near-infrared and Raman spectroscopies and publishes papers dealing with developments in applications, theory, techniques and instrumentation. The topics covered by the journal include: Sampling techniques, Vibrational spectroscopy coupled with separation techniques, Instrumentation (Fourier transform, conventional and laser based), Data manipulation, Spectra-structure correlation and group frequencies. The application areas covered include: Analytical chemistry, Bio-organic and bio-inorganic chemistry, Organic chemistry, Inorganic chemistry, Catalysis, Environmental science, Industrial chemistry, Materials science, Physical chemistry, Polymer science, Process control, Specialized problem solving.
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