Literature DB >> 2281042

A statistical approach for the development of an oral controlled-release matrix tablet.

A D Johnson1, V L Anderson, G E Peck.   

Abstract

Tablet matrix compositions for optimized prolonged release were selected by surface response methodology. The extreme vertices experimental design was used to develop a surface response model which mathematically defined the release of active component from the tablet matrix as controlled by the percentage of the excipient components. The model, a statistical quadratic equation with a standard error of 3.3, was validated for accurate prediction of drug release profiles and used to identify optimum formulations. This study demonstrated a new application of the extreme vertices experimental design, an efficient method for evaluating a complex mixture system for controlled release, where specific constraints are placed on one or more of the components.

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Year:  1990        PMID: 2281042     DOI: 10.1023/a:1015911721455

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  4 in total

1.  Mixture experimental design in the development of a mucoadhesive gel formulation.

Authors:  J S Chu; G L Amidon; N D Weiner; A H Goldberg
Journal:  Pharm Res       Date:  1991-11       Impact factor: 4.200

2.  Application of neural computing in pharmaceutical product development.

Authors:  A S Hussain; X Q Yu; R D Johnson
Journal:  Pharm Res       Date:  1991-10       Impact factor: 4.200

3.  Disintegration mediated controlled release supersaturating solid dispersion formulation of an insoluble drug: design, development, optimization, and in vitro evaluation.

Authors:  Sanjay Verma; Varma S Rudraraju
Journal:  AAPS PharmSciTech       Date:  2014-09-05       Impact factor: 3.246

4.  Mixture design as a first step for optimization of fermentation medium for cutinase production from Colletotrichum lindemuthianum.

Authors:  Fred J Rispoli; Vishal Shah
Journal:  J Ind Microbiol Biotechnol       Date:  2007-02-06       Impact factor: 4.258

  4 in total

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