Artificial Neural Network Combined with Principal Component Analysis for Resolution of Complex Pharmaceutical Formulations
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概要
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A chemometric approach based on the combined use of the principal component analysis (PCA) and artificial neural network (ANN) was developed for the multicomponent determination of caffeine (CAF), mepyramine (MEP), phenylpropanolamine (PPA) and pheniramine (PNA) in their pharmaceutical preparations without any chemical separation. The predictive ability of the ANN method was compared with the classical linear regression method Partial Least Squares 2 (PLS2). The UV spectral data between 220 and 300 nm of a training set of sixteen quaternary mixtures were processed by PCA to reduce the dimensions of input data and eliminate the noise coming from instrumentation. Several spectral ranges and different numbers of principal components (PCs) were tested to find the PCA-ANN and PLS2 models reaching the best determination results. A two layer ANN, using the first four PCs, was used with log-sigmoid transfer function in first hidden layer and linear transfer function in output layer. Standard error of prediction (SEP) was adopted to assess the predictive accuracy of the models when subjected to external validation. PCA-ANN showed better prediction ability in the determination of PPA and PNA in synthetic samples with added excipients and pharmaceutical formulations. Since both components are characterized by low absorptivity, the better performance of PCA-ANN was ascribed to the ability in considering all non-linear information from noise or interfering excipients.
著者
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Dinc Erdal
Department Of Analytical Chemistry Faculty Of Pharmacy Ankara University
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De Luca
Department Of Experimental Medicine Sapienza University
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De Luca
Department Of Clinical And Experimental Medicine Federico 2nd University Of Naples
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Ioele Giuseppina
Department of Pharmaceutical Sciences, University of Calabria
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Oliverio Filomena
Department of Pharmaceutical Sciences, University of Calabria
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Ragno Gaetano
Department of Pharmaceutical Sciences, University of Calabria
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De Luca
Department of Pharmaceutical Sciences, University of Calabria
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