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Optimization of drug release from compressed multi unit particle system (MUPS) using generalized regression neural network (GRNN).
Arch Pharm Res. 2010 Jan; 33(1):103-13.AP

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 accomplished using Carbopol 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 X1-the percentage of polymer Carbopol 71 G and X2-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 X1the percentage of polymer Carbopol 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 which 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%.

Authors+Show Affiliations

Galenika a.d., R&D Institute, Batajnicki drum bb 11080 Belgrade, Serbia. ivicbranka@ikomline.netNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

20191351

Citation

Ivic, Branka, et al. "Optimization of Drug Release From Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN)." Archives of Pharmacal Research, vol. 33, no. 1, 2010, pp. 103-13.
Ivic B, Ibric S, Betz G, et al. Optimization of drug release from compressed multi unit particle system (MUPS) using generalized regression neural network (GRNN). Arch Pharm Res. 2010;33(1):103-13.
Ivic, B., Ibric, S., Betz, G., & Zorica, D. (2010). Optimization of drug release from compressed multi unit particle system (MUPS) using generalized regression neural network (GRNN). Archives of Pharmacal Research, 33(1), 103-13. https://doi.org/10.1007/s12272-010-2232-8
Ivic B, et al. Optimization of Drug Release From Compressed Multi Unit Particle System (MUPS) Using Generalized Regression Neural Network (GRNN). Arch Pharm Res. 2010;33(1):103-13. PubMed PMID: 20191351.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Optimization of drug release from compressed multi unit particle system (MUPS) using generalized regression neural network (GRNN). AU - Ivic,Branka, AU - Ibric,Svetlana, AU - Betz,Gabriele, AU - Zorica,Djuric, Y1 - 2010/02/27/ PY - 2009/07/21/received PY - 2009/10/11/accepted PY - 2009/09/24/revised PY - 2010/3/2/entrez PY - 2010/3/2/pubmed PY - 2010/6/3/medline SP - 103 EP - 13 JF - Archives of pharmacal research JO - Arch Pharm Res VL - 33 IS - 1 N2 - 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 accomplished using Carbopol 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 X1-the percentage of polymer Carbopol 71 G and X2-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 X1the percentage of polymer Carbopol 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 which 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%. SN - 0253-6269 UR - https://www.unboundmedicine.com/medline/citation/20191351/Optimization_of_drug_release_from_compressed_multi_unit_particle_system__MUPS__using_generalized_regression_neural_network__GRNN__ L2 - https://dx.doi.org/10.1007/s12272-010-2232-8 DB - PRIME DP - Unbound Medicine ER -