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Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends

The focus of the present investigation was to develop a predictive dissolution model for tablets coated with blends of cellulose acetate butyrate (CAB) 171-15 and cellulose acetate phthalate (C-A-P) using the design of experiment and chemometric approaches. Diclofenac sodium was used as a model drug...

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Autores principales: Mohamed, Eman M., Khuroo, Tahir, Afrooz, Hamideh, Dharani, Sathish, Sediri, Khaldia, Cook, Phillip, Arunagiri, Rajendran, Khan, Mansoor A., Rahman, Ziyaur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602398/
https://www.ncbi.nlm.nih.gov/pubmed/33076276
http://dx.doi.org/10.3390/ph13100311
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author Mohamed, Eman M.
Khuroo, Tahir
Afrooz, Hamideh
Dharani, Sathish
Sediri, Khaldia
Cook, Phillip
Arunagiri, Rajendran
Khan, Mansoor A.
Rahman, Ziyaur
author_facet Mohamed, Eman M.
Khuroo, Tahir
Afrooz, Hamideh
Dharani, Sathish
Sediri, Khaldia
Cook, Phillip
Arunagiri, Rajendran
Khan, Mansoor A.
Rahman, Ziyaur
author_sort Mohamed, Eman M.
collection PubMed
description The focus of the present investigation was to develop a predictive dissolution model for tablets coated with blends of cellulose acetate butyrate (CAB) 171-15 and cellulose acetate phthalate (C-A-P) using the design of experiment and chemometric approaches. Diclofenac sodium was used as a model drug. Coating weight gain (X(1), 5, 7.5 and 10%) and CAB 171-15 percentage (X(2), 33.3, 50 and 66.7%) in the coating composition relative to C-A-P and were selected as independent variables by full factorial experimental design. The responses monitored were dissolution at 1 (Y(1)), 8 (Y(2)), and 24 (Y(3)) h. Statistically significant (p < 0.05) effects of X(1) on Y(1) and X(2) on Y(1), Y(2,) and Y(3) were observed. The models showed a good correlation between actual and predicted values as indicated by the correlation coefficients of 0.964, 0.914, and 0.932 for Y(1), Y(2,) and Y(3), respectively. For the chemometric model development, the near infrared spectra of the coated tablets were collected, and partial least square regression (PLSR) was performed. PLSR also showed a good correlation between actual and model predicted values as indicated by correlation coefficients of 0.916, 0.964, and 0.974 for Y(1), Y(2), and Y(3), respectively. Y(1), Y(2,) and Y(3) predicted values of the independent sample by both approaches were close to the actual values. In conclusion, it is possible to predict the dissolution of tablets coated with blends of cellulose esters by both approaches.
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spelling pubmed-76023982020-11-01 Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends Mohamed, Eman M. Khuroo, Tahir Afrooz, Hamideh Dharani, Sathish Sediri, Khaldia Cook, Phillip Arunagiri, Rajendran Khan, Mansoor A. Rahman, Ziyaur Pharmaceuticals (Basel) Article The focus of the present investigation was to develop a predictive dissolution model for tablets coated with blends of cellulose acetate butyrate (CAB) 171-15 and cellulose acetate phthalate (C-A-P) using the design of experiment and chemometric approaches. Diclofenac sodium was used as a model drug. Coating weight gain (X(1), 5, 7.5 and 10%) and CAB 171-15 percentage (X(2), 33.3, 50 and 66.7%) in the coating composition relative to C-A-P and were selected as independent variables by full factorial experimental design. The responses monitored were dissolution at 1 (Y(1)), 8 (Y(2)), and 24 (Y(3)) h. Statistically significant (p < 0.05) effects of X(1) on Y(1) and X(2) on Y(1), Y(2,) and Y(3) were observed. The models showed a good correlation between actual and predicted values as indicated by the correlation coefficients of 0.964, 0.914, and 0.932 for Y(1), Y(2,) and Y(3), respectively. For the chemometric model development, the near infrared spectra of the coated tablets were collected, and partial least square regression (PLSR) was performed. PLSR also showed a good correlation between actual and model predicted values as indicated by correlation coefficients of 0.916, 0.964, and 0.974 for Y(1), Y(2), and Y(3), respectively. Y(1), Y(2,) and Y(3) predicted values of the independent sample by both approaches were close to the actual values. In conclusion, it is possible to predict the dissolution of tablets coated with blends of cellulose esters by both approaches. MDPI 2020-10-15 /pmc/articles/PMC7602398/ /pubmed/33076276 http://dx.doi.org/10.3390/ph13100311 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mohamed, Eman M.
Khuroo, Tahir
Afrooz, Hamideh
Dharani, Sathish
Sediri, Khaldia
Cook, Phillip
Arunagiri, Rajendran
Khan, Mansoor A.
Rahman, Ziyaur
Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title_full Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title_fullStr Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title_full_unstemmed Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title_short Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends
title_sort development of a multivariate predictive dissolution model for tablets coated with cellulose ester blends
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602398/
https://www.ncbi.nlm.nih.gov/pubmed/33076276
http://dx.doi.org/10.3390/ph13100311
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