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Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one m...

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Detalles Bibliográficos
Autores principales: Ibrić, Svetlana, Djuriš, Jelena, Parojčić, Jelena, Djurić, Zorica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3834927/
https://www.ncbi.nlm.nih.gov/pubmed/24300369
http://dx.doi.org/10.3390/pharmaceutics4040531
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author Ibrić, Svetlana
Djuriš, Jelena
Parojčić, Jelena
Djurić, Zorica
author_facet Ibrić, Svetlana
Djuriš, Jelena
Parojčić, Jelena
Djurić, Zorica
author_sort Ibrić, Svetlana
collection PubMed
description Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms.
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spelling pubmed-38349272013-11-21 Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms Ibrić, Svetlana Djuriš, Jelena Parojčić, Jelena Djurić, Zorica Pharmaceutics Review Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms. MDPI 2012-10-18 /pmc/articles/PMC3834927/ /pubmed/24300369 http://dx.doi.org/10.3390/pharmaceutics4040531 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Review
Ibrić, Svetlana
Djuriš, Jelena
Parojčić, Jelena
Djurić, Zorica
Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title_full Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title_fullStr Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title_full_unstemmed Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title_short Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms
title_sort artificial neural networks in evaluation and optimization of modified release solid dosage forms
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3834927/
https://www.ncbi.nlm.nih.gov/pubmed/24300369
http://dx.doi.org/10.3390/pharmaceutics4040531
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