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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7602398 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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