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

Created by W.Langdon from gp-bibliography.bib Revision:1.7650

@Article{Aksu:2012:AAPS,

• 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

Citations