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Doctoral Thesis
DOI
https://doi.org/10.11606/T.9.1992.tde-05022015-171039
Document
Author
Full name
Ida Caramico Soares
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 1992
Supervisor
Committee
Helou, Joao Haikal (President)
Fonseca, Maria Jose Vieira
Kedor, Erika Rosa Maria
Lara, Elza Helena Guimaraes
Niero, Rinaldo
Title in Portuguese
Sistemas matriciais - otimização de fórmulas de comprimidos do tipo matriz inerte contendo os agentes tuberculostáticos rifampicina e isoniazida
Keywords in Portuguese
Fármacos
Farmacotécnica
Abstract in Portuguese
Foram desenvolvidas formulações de comprimidos do tipo matriz hidrofílica, contendo hidroxipropilmetil celulose, visando a liberação prolongada de rifampicina e isoniazida. Estudos de biodisponibilidade avaliaram a influência do pH do meio de dissolução da acidificação e alcalinização da matriz da modificação de porosidade e tortuosidade; das técnicas de preparação e da razão fármaco-agente formador da matriz. Os métodos de otimização e de estudos de correlação envolveram um plano experimental com quatro variáveis independentes e cinco níveis para cada uma. Para cada característica analisada foi construída uma equação, por regressão múltipla e a influência de cada variável independente foi analisada através de curvas isoresposta.
Title in English
Matrix systems - formula optimization of inert Matrix type tablets containing agents tuberculosis medication rifampin and isoniazid
Keywords in English
Drugs
Pharmaceutical technology
Abstract in English
It was developed cellulose hidrophilic matrices, in order to provid a controlled release of isoniazid and rifampicin, anti-tuberculosis agents. The study of bioavailability brings to light the influence of the pH of the dissolution medium; of the acidification and alkalinization of the die; of the porosity and tortuosity of the production technic and of the drug-matrix raio. The optimization methods and correlational studies envolved an experimental plan with four independent variable and levels per variable. For each response variable, a multiple regression equation is established and the influence of each independent variable is identified by plotting combined and isoresponse curves.
 
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Publishing Date
2015-02-05
 
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