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Experimental design and multiple response optimization. Using the desirability function in analytical methods development
Open accessAbstract
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 Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function.
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Cites
Box-Behnken design: An alternative for the optimization of analytical methods
Ferreira, S. L. C., Bruns, R. E., Ferreira, H. S., Matos, G. D., David, J. M., Brandão, G. C., da Silva, E. G. P., Portugal, L. A., dos Reis, P. S., Souza, A. S., et al. (2007) · Analytica Chimica Acta · doi:10.1016/j.aca.2007.07.011 · Cited by 3,214
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Metadata
- Authors
- Vera Candioti, L., De Zan, M. M., Cámara, M. S., & Goicoechea, H. C.
- Venue
- Talanta
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 124
- Pages
- 123-138
- ISSN
- 0039-9140 (ISSN-L)
- OpenAlex
- W2060332933
- Cited by
- 1,149
- References
- 1
- FWCI
- 61.61
- Type
- journal article
- Language
- en
- Open access
- green
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- Vera Candioti, L., De Zan, M. M., Cámara, M. S., & Goicoechea, H. C. (2014). Experimental design and multiple response optimization. Using the desirability function in analytical methods development. Talanta. https://doi.org/10.1016/j.talanta.2014.01.034
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