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Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles

The purpose of present study was to optimize rizatriptan (RZT) chitosan (CS) nanoparticles using ionic gelation method by application of quality by design (QbD) approach. Based on risk assessment, effect of three variables, that is CS %, tripolyphosphate % and stirring speed were studied on critical...

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Autores principales: Shirsat, Ajinath Eknath, Chitlange, Sohan S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542404/
https://www.ncbi.nlm.nih.gov/pubmed/26317071
http://dx.doi.org/10.4103/2231-4040.157983
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author Shirsat, Ajinath Eknath
Chitlange, Sohan S.
author_facet Shirsat, Ajinath Eknath
Chitlange, Sohan S.
author_sort Shirsat, Ajinath Eknath
collection PubMed
description The purpose of present study was to optimize rizatriptan (RZT) chitosan (CS) nanoparticles using ionic gelation method by application of quality by design (QbD) approach. Based on risk assessment, effect of three variables, that is CS %, tripolyphosphate % and stirring speed were studied on critical quality attributes (CQAs); particle size and entrapment efficiency. Central composite design (CCD) was implemented for design of experimentation with 20 runs. RZT CS nanoparticles were characterized for particle size, polydispersity index, entrapment efficiency, in-vitro release study, differential scanning calorimetric, X-ray diffraction, scanning electron microscopy (SEM). Based on QbD approach, design space (DS) was optimized with a combination of selected variables with entrapment efficiency > 50% w/w and a particle size between 400 and 600 nm. Validation of model was performed with 3 representative formulations from DS for which standard error of − 0.70–3.29 was observed between experimental and predicted values. In-vitro drug release followed initial burst release 20.26 ± 2.34% in 3–4 h with sustained drug release of 98.43 ± 2.45% in 60 h. Lower magnitude of standard error for CQAs confirms the validation of selected CCD model for optimization of RZT CS nanoparticles. In-vitro drug release followed dual mechanism via, diffusion and polymer erosion. RZT CS nanoparticles were prepared successfully using QbD approach with the understanding of the high risk process and formulation parameters involved and optimized DS with a multifactorial combination of critical parameters to obtain predetermined RZT loaded CS nanoparticle specifications.
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spelling pubmed-45424042015-08-27 Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles Shirsat, Ajinath Eknath Chitlange, Sohan S. J Adv Pharm Technol Res Original Article The purpose of present study was to optimize rizatriptan (RZT) chitosan (CS) nanoparticles using ionic gelation method by application of quality by design (QbD) approach. Based on risk assessment, effect of three variables, that is CS %, tripolyphosphate % and stirring speed were studied on critical quality attributes (CQAs); particle size and entrapment efficiency. Central composite design (CCD) was implemented for design of experimentation with 20 runs. RZT CS nanoparticles were characterized for particle size, polydispersity index, entrapment efficiency, in-vitro release study, differential scanning calorimetric, X-ray diffraction, scanning electron microscopy (SEM). Based on QbD approach, design space (DS) was optimized with a combination of selected variables with entrapment efficiency > 50% w/w and a particle size between 400 and 600 nm. Validation of model was performed with 3 representative formulations from DS for which standard error of − 0.70–3.29 was observed between experimental and predicted values. In-vitro drug release followed initial burst release 20.26 ± 2.34% in 3–4 h with sustained drug release of 98.43 ± 2.45% in 60 h. Lower magnitude of standard error for CQAs confirms the validation of selected CCD model for optimization of RZT CS nanoparticles. In-vitro drug release followed dual mechanism via, diffusion and polymer erosion. RZT CS nanoparticles were prepared successfully using QbD approach with the understanding of the high risk process and formulation parameters involved and optimized DS with a multifactorial combination of critical parameters to obtain predetermined RZT loaded CS nanoparticle specifications. Medknow Publications & Media Pvt Ltd 2015 /pmc/articles/PMC4542404/ /pubmed/26317071 http://dx.doi.org/10.4103/2231-4040.157983 Text en Copyright: © Journal of Advanced Pharmaceutical Technology & Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Shirsat, Ajinath Eknath
Chitlange, Sohan S.
Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title_full Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title_fullStr Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title_full_unstemmed Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title_short Application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
title_sort application of quality by design approach to optimize process and formulation parameters of rizatriptan loaded chitosan nanoparticles
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542404/
https://www.ncbi.nlm.nih.gov/pubmed/26317071
http://dx.doi.org/10.4103/2231-4040.157983
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