FarFaR - Pharmacy Repository
University of Belgrade, Faculty of Pharmacy
    • English
    • Српски
    • Српски (Serbia)
  • English 
    • English
    • Serbian (Cyrillic)
    • Serbian (Latin)
  • Login
View Item 
  •   FarFaR
  • Pharmacy
  • Radovi istraživača / Researchers’ publications
  • View Item
  •   FarFaR
  • Pharmacy
  • Radovi istraživača / Researchers’ publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN)

Authorized Users Only
2010
Authors
Ivić, Branka
Ibrić, Svetlana
Betz, Gabriele
Đurić, Zorica
Article (Published version)
Metadata
Show full item record
Abstract
The purpose of this study was development of diclofenac sodium extended release compressed matrix pellets and optimization using Generalized Regression Neural Network (GRNN). According to Central Composite Design (CCD), ten formulations of diclofenac sodium matrix tablets were prepared. Extended release of diclofenac sodium was acomplished using Carbopol (R) 71G as matrix substance. The process of direct pelletisation and subsequently compression of the pellets into MUPS tablets was applied in order to investigate a different approach in formulation of matrix systems and to achieve more control of the process factors over the principal response - the release of the drug. The investigated factors were X(1) -the percentage of polymer Carbopol (R) 71 G and X(2)- crushing strength of the MUPS tablet. In vitro dissolution time profiles at 5 different sampling times were chosen as responses. Results of drug release studies indicate that drug release rates vary between different formulations,... with a range of 1 hour to 8 hours of dissolution. The most important impact on the drug release has factor X(1) -the percentage of polymer Carbopol (R) 71 G. The purpose of the applied GRNN was to model the effects of these two causal factors on the in vitro release profile of the diclofenac sodium from compressed matrix pellets. The aim of the study was to optimize drug release in manner wich enables following in vitro release of diclofenac sodium during 8 hours in phosphate buffer: 1 h: 15-40%, 2 h: 25-60%, 4 h: 35-75%, 8 h: >70%.

Keywords:
Matrix pellets / Multi unit particle system (MUPS) / Direct pelletization / Diclofenac sodium / Carbopol (R) 71G / Extended release
Source:
Archives of Pharmacal Research, 2010, 33, 1, 103-113
Publisher:
  • Pharmaceutical Soc Korea, Seoul

DOI: 10.1007/s12272-010-2232-8

ISSN: 0253-6269

PubMed: 20191351

WoS: 000274052000014

Scopus: 2-s2.0-77949897807
[ Google Scholar ]
10
6
URI
https://farfar.pharmacy.bg.ac.rs/handle/123456789/1391
Collections
  • Radovi istraživača / Researchers’ publications
Institution/Community
Pharmacy
TY  - JOUR
AU  - Ivić, Branka
AU  - Ibrić, Svetlana
AU  - Betz, Gabriele
AU  - Đurić, Zorica
PY  - 2010
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1391
AB  - The purpose of this study was development of diclofenac sodium extended release compressed matrix pellets and optimization using Generalized Regression Neural Network (GRNN). According to Central Composite Design (CCD), ten formulations of diclofenac sodium matrix tablets were prepared. Extended release of diclofenac sodium was acomplished using Carbopol (R) 71G as matrix substance. The process of direct pelletisation and subsequently compression of the pellets into MUPS tablets was applied in order to investigate a different approach in formulation of matrix systems and to achieve more control of the process factors over the principal response - the release of the drug. The investigated factors were X(1) -the percentage of polymer Carbopol (R) 71 G and X(2)- crushing strength of the MUPS tablet. In vitro dissolution time profiles at 5 different sampling times were chosen as responses. Results of drug release studies indicate that drug release rates vary between different formulations, with a range of 1 hour to 8 hours of dissolution. The most important impact on the drug release has factor X(1) -the percentage of polymer Carbopol (R) 71 G. The purpose of the applied GRNN was to model the effects of these two causal factors on the in vitro release profile of the diclofenac sodium from compressed matrix pellets. The aim of the study was to optimize drug release in manner wich enables following in vitro release of diclofenac sodium during 8 hours in phosphate buffer: 1 h: 15-40%, 2 h: 25-60%, 4 h: 35-75%, 8 h: >70%.
PB  - Pharmaceutical Soc Korea, Seoul
T2  - Archives of Pharmacal Research
T1  - Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN)
VL  - 33
IS  - 1
SP  - 103
EP  - 113
DO  - 10.1007/s12272-010-2232-8
ER  - 
@article{
author = "Ivić, Branka and Ibrić, Svetlana and Betz, Gabriele and Đurić, Zorica",
year = "2010",
abstract = "The purpose of this study was development of diclofenac sodium extended release compressed matrix pellets and optimization using Generalized Regression Neural Network (GRNN). According to Central Composite Design (CCD), ten formulations of diclofenac sodium matrix tablets were prepared. Extended release of diclofenac sodium was acomplished using Carbopol (R) 71G as matrix substance. The process of direct pelletisation and subsequently compression of the pellets into MUPS tablets was applied in order to investigate a different approach in formulation of matrix systems and to achieve more control of the process factors over the principal response - the release of the drug. The investigated factors were X(1) -the percentage of polymer Carbopol (R) 71 G and X(2)- crushing strength of the MUPS tablet. In vitro dissolution time profiles at 5 different sampling times were chosen as responses. Results of drug release studies indicate that drug release rates vary between different formulations, with a range of 1 hour to 8 hours of dissolution. The most important impact on the drug release has factor X(1) -the percentage of polymer Carbopol (R) 71 G. The purpose of the applied GRNN was to model the effects of these two causal factors on the in vitro release profile of the diclofenac sodium from compressed matrix pellets. The aim of the study was to optimize drug release in manner wich enables following in vitro release of diclofenac sodium during 8 hours in phosphate buffer: 1 h: 15-40%, 2 h: 25-60%, 4 h: 35-75%, 8 h: >70%.",
publisher = "Pharmaceutical Soc Korea, Seoul",
journal = "Archives of Pharmacal Research",
title = "Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN)",
volume = "33",
number = "1",
pages = "103-113",
doi = "10.1007/s12272-010-2232-8"
}
Ivić, B., Ibrić, S., Betz, G.,& Đurić, Z.. (2010). Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN). in Archives of Pharmacal Research
Pharmaceutical Soc Korea, Seoul., 33(1), 103-113.
https://doi.org/10.1007/s12272-010-2232-8
Ivić B, Ibrić S, Betz G, Đurić Z. Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN). in Archives of Pharmacal Research. 2010;33(1):103-113.
doi:10.1007/s12272-010-2232-8 .
Ivić, Branka, Ibrić, Svetlana, Betz, Gabriele, Đurić, Zorica, "Optimization of Drug Release from Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN)" in Archives of Pharmacal Research, 33, no. 1 (2010):103-113,
https://doi.org/10.1007/s12272-010-2232-8 . .

DSpace software copyright © 2002-2015  DuraSpace
About FarFaR - Pharmacy Repository | Send Feedback

OpenAIRERCUB
 

 

All of DSpaceCommunitiesAuthorsTitlesSubjectsThis institutionAuthorsTitlesSubjects

Statistics

View Usage Statistics

DSpace software copyright © 2002-2015  DuraSpace
About FarFaR - Pharmacy Repository | Send Feedback

OpenAIRERCUB