Near InfraRed Spectroscopy homogeneity evaluation of complex powder blends in a small-scale pharmaceutical preformulation process, a real-life application

Storme-Paris, I.; Clarot, I.; Esposito, Serena; Chaumeil, Jean‐Claude; Nicolas, Alice; Brion, F.; Rieutord, André; Chaminade, Pierre

doi:10.1016/j.ejpb.2008.11.002

Cited by 28 publications

(11 citation statements)

References 26 publications

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“…In this research, both FT-IR and FT-NIR spectral data were treated with several different preprocessing methods, namely, mean normalization, range normalization, standard normal variate, multiplicative scatter correction (MSC), standard normal variate (SNV), and Savitzky–Golay (SG) derivatives (1st and 2nd). For a detailed description of the various preprocessing methods, refer to [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

Comparative Determination of Phenolic Compounds in Arabidopsis thaliana Leaf Powder under Distinct Stress Conditions Using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

Joshi

Sathasivam

Kumar

et al. 2022

Plants

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The increasing interest in plant phenolic compounds in the past few years has become necessary because of their several important physicochemical properties. Thus, their identification through non-destructive methods has become crucial. This study carried out comparative non-destructive measurements of Arabidopsis thaliana leaf powder sample phenolic compounds using Fourier-transform infrared and near-infrared spectroscopic techniques under six distinct stress conditions. The prediction analysis of 600 leaf powder samples under different stress conditions (LED lights and drought) was performed using PLSR, PCR, and NAS-based HLA/GO regression analysis methods. The results obtained through FT-NIR spectroscopy yielded the highest correlation coefficient (Rp2) value of 0.999, with a minimum error (RMSEP) value of 0.003 mg/g, based on the PLSR model using the MSC preprocessing method, which was slightly better than the correlation coefficient (Rp2) value of 0.980 with an error (RMSEP) value of 0.055 mg/g for FT-IR spectroscopy. Additionally, beta coefficient plots present spectral differences and the identification of important spectral signatures sensitive to the phenolic compounds in the measured powdered samples. Thus, the obtained results demonstrated that FT-NIR spectroscopy combined with partial least squares regression (PLSR) and suitable preprocessing method has a solid potential for non-destructively predicting phenolic compounds in Arabidopsis thaliana leaf powder samples.

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Section: Methodsmentioning

confidence: 99%

Comparative Determination of Phenolic Compounds in Arabidopsis thaliana Leaf Powder under Distinct Stress Conditions Using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

Joshi

Sathasivam

Kumar

et al. 2022

Plants

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“…For this research, the raw data were pretreated using several preprocessing methods, including multiplicative scatter correction (MSC), standard normal variate (SNV), and Savitzky-Golay (SG) filtering. MSC and SNV are the most commonly used preprocessing methods to remove background, slope variation, and scattering effects from the spectral data [23]. Furthermore, Savitzky-Golay filters (first and second derivative) methods were used to eliminate the undesired effects, such as noise and baseline drift, from the obtained FT-IR spectroscopic data [24,25].…”

Section: Data Preprocessing and Multivariate Analysismentioning

confidence: 99%

Application of Fourier Transform Infrared Spectroscopy and Multivariate Analysis Methods for the Non-Destructive Evaluation of Phenolics Compounds in Moringa Powder

et al. 2021

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This study performed non-destructive measurements of phenolic compounds in moringa powder using Fourier Transform Infrared (FT-IR) spectroscopy within a spectral range of 3500–700 cm−1. Three major phenolic compounds, namely, kaempferol, benzoic acid, and rutin, were measured in five different varieties of moringa powder, which was approved with respect to the high-performance liquid chromatography (HPLC) method. The prediction performance of three different regression methods, i.e., partial least squares regression (PLSR), principal component regression (PCR), and net analyte signal (NAS)-based methodology, called hybrid linear analysis (HLA/GO), were compared to achieve the best prediction model. The obtained results for the PLS regression method resulted in better performance for the prediction analysis of phenolic compounds in moringa powder. The PLSR model attained a correlation coefficient () value of 0.997 and root mean square error of prediction (RMSEP) of 0.035 mg/g, respectively, which is comparatively higher than the other two regression models. Based on the results, it can be concluded that FT-IR spectroscopy in conjugation with a suitable regression analysis method could be an effective analytical tool for the non-destructive prediction of phenolic compounds in moringa powder.

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“…NIRS combined with different data processing methods served a useful tool for the qualitative and quantitative determination of components, also in blends [90].…”

Section: Quantitative Investigations and Statistical Analysismentioning

confidence: 99%

Infrared-Spectroscopy: A Non-Invasive Tool for Medical Diagnostics and Drug Analysis

Hahn

Pallua²,

Pezzei³

et al. 2010

CMC

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Constant development enabled Infrared (IR) spectroscopy to become a widely used, non-invasive tool for fast sample analyses with less to no pre-preparation. Furthermore, computational data handling is no more a limiting factor and hence, IR measurements are predestined for clinical diagnostics and drug analysis. Within this review the focus was put on clinical topics of high interest. One example is Alzheimer's disease, where the exact metabolism is still not clarified, or blood glucose monitoring for high throughput screening of patients without taking any drop of blood. The second section of this manuscript was focused on the analysis of drugs. The detection of physico-chemical parameters in pharmaceutics and the improvement of industrial proceedings allowed a dramatic increase of quality of produced medicine. In pharmaceutical industries problems with the equable allocation of agents occurs especially in scaling up processes. IR-analyzing-techniques serve as fast and precise indicators for the detection of active components and their distribution in tablets. In combination with statistical factors and medical investigations pharmaceuticals can be improved from their development until their application, and every step can be easily controlled by IR spectroscopy.

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Near InfraRed Spectroscopy homogeneity evaluation of complex powder blends in a small-scale pharmaceutical preformulation process, a real-life application

Cited by 28 publications

References 26 publications

Comparative Determination of Phenolic Compounds in Arabidopsis thaliana Leaf Powder under Distinct Stress Conditions Using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

Comparative Determination of Phenolic Compounds in Arabidopsis thaliana Leaf Powder under Distinct Stress Conditions Using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

Application of Fourier Transform Infrared Spectroscopy and Multivariate Analysis Methods for the Non-Destructive Evaluation of Phenolics Compounds in Moringa Powder

Infrared-Spectroscopy: A Non-Invasive Tool for Medical Diagnostics and Drug Analysis

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