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    Data mining of fractured experimental data using neurofuzzy logic-discovering and integrating knowledge hidden in multiple formulation databases for a fluid-bed granulation process.

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    Publication date
    2008
    Author
    Shao, Qun
    Rowe, Raymond C.
    York, Peter
    Keyword
    Pharmaceutical technology
    Process
    Granulation
    Database
    Formulation
    Knowledge
    Data mining
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    In the pharmaceutical field, current practice in gaining process understanding by data analysis or knowledge discovery has generally focused on dealing with single experimental databases. This limits the level of knowledge extracted in the situation where data from a number of sources, so called fractured data, contain interrelated information. This situation is particularly relevant for complex processes involving a number of operating variables, such as a fluid-bed granulation. This study investigated three data mining strategies to discover and integrate knowledge "hidden" in a number of small experimental databases for a fluid-bed granulation process using neurofuzzy logic technology. Results showed that more comprehensive domain knowledge was discovered from multiple databases via an appropriate data mining strategy. This study also demonstrated that the textual information excluded in individual databases was a critical parameter and often acted as the precondition for integrating knowledge extracted from different databases. Consequently generic knowledge of the domain was discovered, leading to an improved understanding of the granulation process.
    URI
    http://hdl.handle.net/10454/3439
    Version
    No full-text available in the repository
    Citation
    Shao, Q., Rowe, C. and York, P. (2008). Data mining of fractured experimental data using neurofuzzy logic-discovering and integrating knowledge hidden in multiple formulation databases for a fluid-bed granulation process. Journal of Pharmaceutical Sciences. Vol. 97, No. 6, pp. 2091-2101.
    Link to publisher’s version
    http://dx.doi.org/10.1002/jps.21098
    Type
    Article
    Collections
    Life Sciences Publications

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