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新的化学计量学辅助分光光度法同时测定不同剂型组合中共同配制的药物孟鲁司特、卢帕他定和地氯雷他定。

New chemometrics-assisted spectrophotometric methods for simultaneous determination of co-formulated drugs montelukast, rupatadine, and desloratadine in their different dosage combinations.

作者信息

Sharkawi Marco M Z, Farid Nehal F, Hassan Moataz H, Hassan Said A

机构信息

Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Beni-Suef University, Alshaheed Shehata Ahmad Hegazy St, Beni-Suef, 62514, Egypt.

Pharmaceutical Analytical Chemistry Department, College of Pharmaceutical Sciences and Drug Manufacturing, Misr University for Science and Technology, 6th of October City, 12566, Giza, Egypt.

出版信息

BMC Chem. 2024 Nov 19;18(1):232. doi: 10.1186/s13065-024-01345-6.

Abstract

Two accurate, precise and robust multivariate chemometric methods were developed for the simultaneous determination of montelukast sodium (MON), rupatadine fumarate (RUP) and desloratadine (DES). These methods provide a cost-effective alternative to chromatographic techniques by utilizing spectrophotometry in pharmaceutical quality control. The proposed approaches, partial least squares-1 (PLS-1) and artificial neural network (ANN), were optimized using genetic algorithm (GA) to select the most influential wavelengths, enhancing model performance. A five-level, three-factor design was employed to construct a calibration set with 25 mixtures, utilizing concentration ranges of 3-19, 5-25, and 4-20 µg.mL for MON, RUP, and DES, respectively. An independent validation set was employed to assess the performance of the models. GA significantly improved the PLS-1 and ANN models for RUP and DES, though minimal enhancement was observed for MON. These methods were successfully applied to the simultaneous quantification of the compounds in pharmaceutical formulations and proved useful as stability-indicating assays for RUP, given that DES is a known degradation product. The developed methods offer a valuable tool for impurity profiling and quality control in pharmaceutical analysis.

摘要

开发了两种准确、精密且稳健的多元化学计量学方法,用于同时测定孟鲁司特钠(MON)、富马酸卢帕他定(RUP)和地氯雷他定(DES)。这些方法通过在药物质量控制中利用分光光度法,为色谱技术提供了一种经济高效的替代方法。所提出的方法,偏最小二乘法-1(PLS-1)和人工神经网络(ANN),使用遗传算法(GA)进行优化,以选择最具影响力的波长,从而提高模型性能。采用五级三因素设计构建了一个包含25种混合物的校准集,MON、RUP和DES的浓度范围分别为3 - 19、5 - 25和4 - 20 μg/mL。使用独立验证集评估模型的性能。GA显著改善了RUP和DES的PLS-1和ANN模型,尽管对MON的增强作用最小。这些方法成功应用于药物制剂中化合物的同时定量,并且鉴于DES是已知的降解产物,被证明对RUP是有效的稳定性指示分析方法。所开发的方法为药物分析中的杂质剖析和质量控制提供了一个有价值的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b570/11574986/818392109e85/13065_2024_1345_Fig1_HTML.jpg

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