Quality by Design Approach: Application of Artificial Intelligence Techniques of Tablets Manufactured by Direct Compression

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Buket Aksu and Anant Paradkar and Marcel Matas and 
                 Ozgen Ozer and Tamer Guneri and Peter York",
  title =        "Quality by Design Approach: Application of Artificial
                 Intelligence Techniques of Tablets Manufactured by
                 Direct Compression",
  journal =      "AAPS PharmSciTech",
  year =         "2012",
  volume =       "13",
  number =       "4",
  pages =        "1138--1146",
  month =        sep # "~06",
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, artificial neural networks,
                 ANNs, GEP, optimisation, quality by design (qbd)",
  DOI =          "doi:10.1208/s12249-012-9836-x",
  URL =          "http://dx.doi.org/10.1208/s12249-012-9836-x",
  URL =          "http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3513460",
  URL =          "http://www.ncbi.nlm.nih.gov/pubmed/22956056",
  language =     "English",
  bibsource =    "OAI-PMH server at www.ncbi.nlm.nih.gov",
  oai =          "oai:pubmedcentral.nih.gov:3513460",
  publisher =    "American Association of Pharmaceutical Scientists",
  abstract =     "The publication of the International Conference of
                 Harmonization (ICH) Q8, Q9, and Q10 guidelines paved
                 the way for the standardization of quality after the
                 Food and Drug Administration issued current Good
                 Manufacturing Practices guidelines in 2003. Quality by
                 Design, mentioned in the ICH Q8 guideline, offers a
                 better scientific understanding of critical process and
                 product qualities using knowledge obtained during the
                 life cycle of a product. In this scope, the knowledge
                 space is a summary of all process knowledge obtained
                 during product development, and the design space is the
                 area in which a product can be manufactured within
                 acceptable limits. To create the spaces, artificial
                 neural networks (ANNs) can be used to emphasise the
                 multidimensional interactions of input variables and to
                 closely bind these variables to a design space. This
                 helps guide the experimental design process to include
                 interactions among the input variables, along with
                 modelling and optimisation of pharmaceutical
                 formulations. The objective of this study was to
                 develop an integrated multivariate approach to obtain a
                 quality product based on an understanding of the
                 cause--effect relationships between formulation
                 ingredients and product properties with ANNs and
                 genetic programming on the ramipril tablets prepared by
                 the direct compression method. In this study, the data
                 are generated through the systematic application of the
                 design of experiments (DoE) principles and optimisation
                 studies using artificial neural networks and neurofuzzy
                 logic programs.",

Genetic Programming entries for Buket Aksu Anant Paradkar Marcel Matas Ozgen Ozer Tamer Guneri Peter York