Environmentally sustainable DRS-FTIR probe assisted by chemometric tools for quality control analysis of cinnarizine and piracetam having diverged concentration ranges: Validation, greenness, and whiteness studies.

Cinnarizine DRS-FTIR Green analytical chemistry PLSR chemometrics Piracetam White analytical chemistry

Journal

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
ISSN: 1873-3557
Titre abrégé: Spectrochim Acta A Mol Biomol Spectrosc
Pays: England
ID NLM: 9602533

Informations de publication

Date de publication:
05 Dec 2023
Historique:
received: 25 01 2023
revised: 11 07 2023
accepted: 13 07 2023
medline: 7 9 2023
pubmed: 22 7 2023
entrez: 21 7 2023
Statut: ppublish

Résumé

A novel diffuse reflectance fourier transform infrared spectroscopic method accompanied by chemometrics was optimized to fulfill the white analytical chemistry and green analytical chemistry principles for the quantification of cinnarizine and piracetam for the first time without any prior separation in their challenging pharmaceutical preparation, which has a pretty substantial difference in the concentration of cinnarizine/piracetam (1:16). Furthermore, the suggested method was used for cinnarizine/piracetam dissolution testing as an effective alternative to traditional methods. For the cinnarizine/piracetam dissolution tests, we used a dissolution vessel with 900 mL of phosphate buffer pH 2.5 at 37 °C ± 0.5 °C, then the sampling was carried out by frequent withdrawal of 20 µl samples from the dissolution vessel at a one-minute interval, over one hour, then representative fourier transform infrared spectra were recorded. To create a partial-least-squares regression model, a fractional factorial design with 5 different levels and 2 factors was used. This led to the creation of 25 mixtures, 15 as a calibration set and 10 as a validation set, with varying concentration ranges: 1-75 and 16-1000 μg/mL for cinnarizine/piracetam, respectively. Upon optimization of the partial-least-squares regression model, in terms of latent variables and spectral region, root mean square error of cross-validation of 0.477 and 0.270, for cinnarizine/piracetam respectively, were obtained. The optimized partial-least-squares regression model was further validated, providing good results in terms of recovery% (around 98 to 102 %), root mean square error of prediction (0.436 and 3.329), relative root mean square error of prediction (1.210 and 1.245), bias-corrected mean square error of prediction (0.059 and 0.081), and limit of detection (0.125 and 2.786) for cinnarizine/piracetam respectively. Ultimately, the developed method was assessed for whiteness, greenness, and sustainability using five assessment tools. the developed method achieved a greener national environmental method index and complementary green analytical procedure index quadrants with higher eco-scale assessment scores (91), analytical greenness metric scores (0.87), and red-greenblue 12 algorithm scores (89.7) than the reported methods, showing high practical and environmental acceptance for quality control of cinnarizine/piracetam.

Identifiants

pubmed: 37478754
pii: S1386-1425(23)00846-6
doi: 10.1016/j.saa.2023.123161
pii:
doi:

Substances chimiques

Cinnarizine 3DI2E1X18L
Piracetam ZH516LNZ10

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

123161

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Khalid A M Attia (KAM)

Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt.

Ahmed El-Olemy (A)

Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt.

Ahmed Serag (A)

Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, 11751 Nasr City, Cairo, Egypt.

Ahmed Emad F Abbas (AEF)

Analytical Chemistry Department, Faculty of Pharmacy, October 6 University, 6 October City, Giza 12585, Egypt.

Sherif M Eid (SM)

Analytical Chemistry Department, Faculty of Pharmacy, October 6 University, 6 October City, Giza 12585, Egypt. Electronic address: sheriefmohammed@o6u.edu.eg.

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Classifications MeSH