Literature DB >> 11839449

Optimization and characterization of controlled release multi-particulate beads formulated with a customized cellulose acetate butyrate dispersion.

Siva Vaithiyalingam1, Mansoor A Khan.   

Abstract

The objectives of the present investigation were: (1) to model the effect of process and formulation variables viz., coating weight gain, duration of curing, and plasticizer concentration on in-vitro release profile of verapamil HCl from multi-particulate beads formulated with a novel aqueous-based pseudolatex dispersion; (2) to optimize the formulation by response surface methodology (RSM) and artificial neural network (ANN); and (3) to characterize the optimized product by thermal and X-ray analyses. Inert beads (Nupareil) were loaded with verapamil HCl and subsequently coated with a custom designed aqueous-based pseudolatex dispersion of cellulose acetate butyrate (CAB). Experiments were designed and data was collected according to a three factor, three level face centered central composite design. Data was analyzed for modeling and optimizing the release profile using both RSM and ANN. Model fitted the data and explained 90% of variability in response in the case of RSM and at least 70% in the case of ANN. Release profile was optimized for a zero-order model. Optimized formulations were prepared according to the factor combinations dictated by RSM and ANN. In each case, the observed drug release data of the optimized formulations was close to the predicted release pattern. However, the modeling and optimization abilities of RSM as evaluated by the R-squared values, were found to be higher than that of ANN. X-ray and drug content analysis suggested the absence of any degradation of verapamil HCl and excipients incorporated in the formulation.

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Year:  2002        PMID: 11839449     DOI: 10.1016/s0378-5173(01)00959-0

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  2 in total

1.  Introduction of a mathematical model for optimizing the drug release in the patient's body.

Authors:  Mohammad Reza Nabatchian; Hamid Shahriari; Mona Shahriari
Journal:  Daru       Date:  2014-01-03       Impact factor: 3.117

2.  Artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Authors:  Svetlana Ibrić; Jelena Djuriš; Jelena Parojčić; Zorica Djurić
Journal:  Pharmaceutics       Date:  2012-10-18       Impact factor: 6.321

  2 in total

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