Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model

IF 0.7 Q4 CHEMISTRY, ANALYTICAL Methods and Objects of Chemical Analysis Pub Date : 2022-01-01 DOI:10.17721/moca.2022.118-124
Azhar S. Hamody, F. Zankanah, S. Ali, N. Alassaf, S. B. Dikran
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Abstract

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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基于人工神经网络模型的四元药物混合物分光光度分析
建立了一种新的人工神经网络(ANN)模型,对卡马西平、卡维地洛、地西泮和呋塞米组成的季元混合物的同时定量分析的多元模型进行了校正。用分光光度法制备和分析了84混合配方。每种分析物在六个不同浓度的样品中配制,因此对四种分析物的24个样品进行了测试。一个由10个隐藏神经元组成的神经网络能够100%拟合数据。该模型可用于四元混合料的定量化学分析。
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来源期刊
CiteScore
1.00
自引率
14.30%
发文量
12
期刊介绍: The journal "Methods and objects of chemical analysis" is peer-review journal and publishes original articles of theoretical and experimental analysis on topical issues and bio-analytical chemistry, chemical and pharmaceutical analysis, as well as chemical metrology. Submitted works shall cover the results of completed studies and shall make scientific contributions to the relevant area of expertise. The journal publishes review articles, research articles and articles related to latest developments of analytical instrumentations.
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