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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

NIR hyperspectral imaging to evaluate degradation in captopril commercial tablets

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Autor(es):
Franca, Leandro de Moura [1] ; Pimentel, Maria Fernanda [2] ; Simoes, Simone da Silva [3] ; Grangeiro, Jr., Severino [4] ; Prats-Montalban, Jose M. [5] ; Ferrer, Alberto [5]
Número total de Autores: 6
Afiliação do(s) autor(es):
[1] Univ Fed Pernambuco, Dept Quim Fundamental, Prof Moraes Rego 1235, Cidade Univ, BR-50670901 Recife, PE - Brazil
[2] Univ Fed Pernambuco, Dept Engn Quim, Av Artur de Sa S-N, Cidade Univ, BR-50740521 Recife, PE - Brazil
[3] Univ Estadual Paraiba, BR-58429500 Campina Grande, Paraiba - Brazil
[4] Lab Farmaceut Estado Pernambuco Miguel Arraes, Largo Dois Irmaos 1117, BR-52171010 Recife, PE - Brazil
[5] Univ Politecn Valencia, Camino Vera S-N, Edificio 7A, E-46022 Valencia - Spain
Número total de Afiliações: 5
Tipo de documento: Artigo Científico
Fonte: EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS; v. 104, p. 180-188, JUL 2016.
Citações Web of Science: 5
Resumo

Pharmaceutical quality control is important for improving the effectiveness, purity and safety of drugs, as well as for the prevention or control of drug degradation. In the present work, near infrared hyperspectral images (HSI-NIR) of tablets with different expiration dates were employed to evaluate the degradation of captopril into captopril disulfide in different layers, on the top and on the bottom surfaces of the tablets. Multivariate curve resolution (MCR) models were used to extract the concentration distribution maps from the hyperspectral images. Afterward, multivariate image techniques were applied to the concentration distribution maps (CDMs), to extract features and build models relating the main characteristics of the images to their corresponding manufacturing dates. Resolution methods followed by extracting features were able to estimate the tablet manufacture date with a prediction error of 120 days. The model developed could be useful to evaluate whether a sample shows a degradation pattern consistent with the date of manufacturing or to detect abnormal behaviors in the natural degradation process of the sample. The information provided by the HIS-NIR is important for the development of the process (QbD), looking inside the formulation, revealing the behavior of the active pharmaceutical ingredient (API) during the product's shelf life. (C) 2016 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 08/57808-1 - Instituto Nacional de Ciências e Tecnologias Analíticas Avançadas - INCTAA
Beneficiário:Celio Pasquini
Modalidade de apoio: Auxílio à Pesquisa - Temático