Literature DB >> 20667507

Multivariate wavelet texture analysis for pharmaceutical solid product characterization.

Salvador García-Muñoz1, Alan Carmody.   

Abstract

The application of multivariate wavelet texture analysis (MWTA) is presented and discussed as it is applied to three different types of pharmaceutical materials: (a) tablet cores, (b) wet granules and (c) controlled release tablets. The application of MWTA is initially proposed as a quantitative replacement to the human visual judgment of the textural appearance of the different materials. In all cases, the metrics obtained with MWTA agree with visual assessment on the progression of textural features such as erosion and surface roughness. This work further demonstrates that MWTA also represents a useful tool to increase the understanding of the manufacturing process, as it provides diagnostics to relate process parameters with textural features of the material that are difficult or costly to measure otherwise (such as granule size for wet material or surface appearance for a controlled release product). MWTA is also presented as a potential tool for real-time release for those cases where the textural features can be proven to provide accurate enough predictions of the final product performance; as shown here with the obtained prediction of dissolution from the controlled release tablet using the texture of the product as an input. Copyright 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20667507     DOI: 10.1016/j.ijpharm.2010.07.032

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


  2 in total

1.  Image analysis quantification of sticking and picking events of pharmaceutical powders compressed on a rotary tablet press simulator.

Authors:  Germinal Mollereau; Vincent Mazel; Virginie Busignies; Pierre Tchoreloff; Fabrice Mouveaux; Philippe Rivière
Journal:  Pharm Res       Date:  2013-09       Impact factor: 4.200

2.  Fast tablet tensile strength prediction based on non-invasive analytics.

Authors:  Anna Halenius; Satu Lakio; Osmo Antikainen; Juha Hatara; Jouko Yliruusi
Journal:  AAPS PharmSciTech       Date:  2014-03-18       Impact factor: 3.246

  2 in total

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