Advanced chemometrics manipulation of UV-spectroscopic data for determination of three co-formulated drugs along with their impurities in different formulations using variable selection and regression model updating

Hegazy, Maha A.; Boltia, Shereen A.; Fayed, Ahmed S.; Musaed, Awadh

doi:10.1016/j.saa.2018.05.038

Cited by 8 publications

(6 citation statements)

References 14 publications

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“…In addition, the independent subinterval model with the minimum RMSECV is selected and serves as the optimum modeling interval. The optimal models of subintervals and the whole spectral model were compared 20,21,22 …”

Section: Methodsmentioning

confidence: 99%

“…The optimal models of subintervals and the whole spectral model were compared. 20,21,22 Adaptive reweighted sampling The CARS method is mainly applied to eliminate useless or irrelevant spectral variables with the aim of establishing the classification model with high performance. 23 Its principle is the survival of the fittest of Evolution Theory.…”

Section: Sample Preparationmentioning

confidence: 99%

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Simultaneous sex and species classification of silkworm pupae by NIR spectroscopy combined with chemometric analysis

et al. 2020

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BACKGROUND Most studies only focus on the sex discrimination of silkworm pupae. However, species differentiation of silkworm pupae is also needed in sericulture. To classify the sex and species at the same time, the present study adopts near infrared (NIR) spectroscopy combined with multivariate analysis. RESULTS First, spectra samples were acquired using an NIR sensor, comprising female and male silkworm pupae from three species. Second, three different variables selection approaches were used, including a successive projections algorithm, competitive adaptive reweighted sampling (CARS) and interval partial least squares (iPLS). Third, identification models were built based on random forest and partial least squares discriminant analysis (PLSDA). The experimental results show that iPLS‐PLSDA model (95.24%) gives a high performance when using the one of the three variable selection methods alone. To further increase the performance, the variable selection methods are optimized. The accuracy of the iPLS‐CARS‐PLSDA model is as high as 98.41%. CONCLUSION The present study demonstrates that the optimized variable selection method in combination with NIR spectroscopy represents a suitable strategy for sex and species identification of silkworm pupae. © 2020 Society of Chemical Industry

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Section: Methodsmentioning

confidence: 99%

Section: Sample Preparationmentioning

confidence: 99%

Simultaneous sex and species classification of silkworm pupae by NIR spectroscopy combined with chemometric analysis

et al. 2020

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“…PLS is the predictive chemometric algorithm used for the separation and resolution of complex mixture being well recognized depending on factor analysis [14]. PLS deals with the full raw spectral data for building the model where the optimum number of latent variables was chosen according to Haaland and Thomas criteria [17,18]. Cross validation and an external validation set were used to test the developed model.…”

Section: Partial Least Squaresmentioning

confidence: 99%

“…As the full spectral data using simple univariate spectrophotometry failed for efficient determination and explanation of the complex systems, variables (wavelengths) selection could improve such resolution in the points of collinearity and can improve prediction ability through finding out the most informative regions in spectra [18]. Thus, more efficient determination with lower number of LVs could be obtained.…”

Section: Variables Selection Algorithmsmentioning

confidence: 99%

“…A number of equidistant intervals which is variable wise are formed by siPLS [18,20] via dividing the data sets, and then calculating all possible PLS models from a combination of two, three or four intervals. Many models were processed depending on the number of intervals and the selected number of intervals to be combined.…”

Section: Synergy Interval Partial Least Squaresmentioning

confidence: 99%

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Pure component contribution (PCCA) and synergy interval partial least squares (siPLS) algorithms for efficient resolution and quantification of overlapped signals; an application to novel antiviral tablets of daclatasvir, sofosbuvir and ribavirin

et al. 2019

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Daclatasvir (DAC), sofosbuvir (SOF) and ribavirin (RIB) have been recently co-formulated in tablet dosage form for the treatment of Hepatitis C virus infections. In this work, the resolution and quantitation of overlapped spectral signals was achieved by both univariate and multivariate algorithms. Pure component contribution algorithm (PCCA) as a novel approach was applied along with factor based partial least squares (PLS) algorithms using both full range and synergistic intervals (siPLS). Each drug could be determined at its λmax using PCCA, while PLS and siPLS were used for multivariate determination of the three components. Good linear relationships were obtained in the ranges of 5.45-16.35, 4.40-44.00 and 5.50-35.00 µg/mL for DAC, SOF and RIB, respectively, by PCCA. The PLS and siPLS models were built for the three compounds each in the concentration range of 2.00-10.00, 10.00-20.00 and 10.00-26.00 µg/mLfor DAC, SOF and RIB, respectively. Validation of the proposed methods was ascertained according to ICH guidelines for PCCA and through the use of internal and external validation sets for PLS and SiPLS models. The three methods were successfully applied for determination of DAC, SOF and RIB in pure form and in tablets.

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Cost-effective and earth-friendly chemometrics-assisted spectrophotometric methods for simultaneous determination of Acetaminophen and Ascorbic Acid in pharmaceutical formulation

Lalaouna

Hadef

Nekkaa

et al. 2022

Spectrochimica Acta Part A: Molecular and Biomolecular Spectros

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Advanced chemometrics manipulation of UV-spectroscopic data for determination of three co-formulated drugs along with their impurities in different formulations using variable selection and regression model updating

Cited by 8 publications

References 14 publications

Simultaneous sex and species classification of silkworm pupae by NIR spectroscopy combined with chemometric analysis

Simultaneous sex and species classification of silkworm pupae by NIR spectroscopy combined with chemometric analysis

Pure component contribution (PCCA) and synergy interval partial least squares (siPLS) algorithms for efficient resolution and quantification of overlapped signals; an application to novel antiviral tablets of daclatasvir, sofosbuvir and ribavirin

Cost-effective and earth-friendly chemometrics-assisted spectrophotometric methods for simultaneous determination of Acetaminophen and Ascorbic Acid in pharmaceutical formulation

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