Literature DB >> 29521132

A novel and discriminative method of in vitro disintegration time for preparation and optimization of taste-masked orally disintegrating tablets of carbinoxamine maleate.

Yali Liu1, Peng Li1, Rong Qian2, Tianyu Sun2, Fangzhi Fang2, Zonghua Wang2, Xue Ke1, Bohui Xu3.   

Abstract

The primary objective of this study was to mask bitter taste and decrease the disintegration time of carbinoxamine maleate (CAM) orally disintegrating tablets (ODTs). In order to screen the prescription of ODTs, a novel modified in vitro disintegration method (MIVDM) was developed to measure the in vitro disintegration time. In this method, different concentrations of ethanol served as disintegration medium in order to delay the in vitro water absorption and disintegration process of tablets. The MIVDM demonstrated good in vitro and in vivo correlation and proved more precise and discriminative than other reported methods. In this research, ion exchange resins (IERs) were used to mask bitter taste for improving mouthfeel. The drug-resin ratio and reaction temperature were investigated to obtain the optimum carbinoxamine resin complexes (CRCs). The characterization of CRCs revealed an amorphous state. ODTs were prepared by direct compression. Superdisintegrants and diluents of ODTs were screened first. Further optimization was carried out by using Box-Behnken design. The effect of (X1) mannitol/microcrystalline cellulose ratio, (X2) the amount of low-substituted hydroxypropylcellulose and (X3) the hardness was investigated for achieving the lowest (Y) in vitro disintegration time. Technological characterization, wetting time, water absorption ratio, and roughness degree were evaluated. The CRCs and ODTs proved successful taste-masking efficiency. The end product improved patients' compliance. The developed MIVDM was practical for commercial use.

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Keywords:  Box–Behnken design; Ion exchange resin; in vitro/in vivo disintegration time; oral disintegrating tablets; taste masking

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Year:  2018        PMID: 29521132     DOI: 10.1080/03639045.2018.1449854

Source DB:  PubMed          Journal:  Drug Dev Ind Pharm        ISSN: 0363-9045            Impact factor:   3.225


  1 in total

1.  Puzzle out Machine Learning Model-Explaining Disintegration Process in ODTs.

Authors:  Jakub Szlęk; Mohammad Hassan Khalid; Adam Pacławski; Natalia Czub; Aleksander Mendyk
Journal:  Pharmaceutics       Date:  2022-04-13       Impact factor: 6.525

  1 in total

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