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Experimental design and multiple response optimization. Using the desirability function in analytical methods development

期刊

TALANTA
卷 124, 期 -, 页码 123-138

出版社

ELSEVIER
DOI: 10.1016/j.talanta.2014.01.034

关键词

Experimental design; Response transformation; Multiple response optimization; Desirability function

资金

  1. Universidad Nacional del Litoral (Projects CAI+D 2011) [11-11, 11-25, 11-14]
  2. CONICET (Consejo Nacional de Investigaciones Cientificas y Tecnicas Project PIP-2012 [455]
  3. ANPCyT (Agencia Nacional de Promocion Cientifica y Tecnologica, Project PICT) [2011-0005]

向作者/读者索取更多资源

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquimica y Ciencias Biologicas, Universidad Nacional del Litoral, CC. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. (C) 2014 Elsevier BM. All rights reserved.

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