A review of multivariate calibration methods applied to biomedical analysis

Autores
Escandar, Graciela Monica; Damiani, Patricia Cecilia; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar
Año de publicación
2006
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate calibration methods constitute an attractive alternative, even when they are applied to intrinsically unselective spectroscopic or electrochemical signals. First-order (i.e., vectorized) data are conveniently analyzed with classical chemometric tools such as partial least-squares (PLS). Certain analytical problems require more sophisticated models, such as artificial neural networks (ANNs), which are especially able to cope with non-linearities in the data structure. Finally, models based on the acquisition and processing of second- or higher-order data (i.e., matrices or higher dimensional data arrays) present the phenomenon known as "second-order advantage", which permits quantitation of calibrated analytes in the presence of interferents. The latter models show immense potentialities in the field of biomedical analysis. Pertinent literature examples are reviewed.
Fil: Escandar, Graciela Monica. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Damiani, Patricia Cecilia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Materia
BIOMEDICAL ANALYSIS
FIRST- AND HIGHER-ORDER DATA
MULTIVARIATE CALIBRATION METHODS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/151001
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A review of multivariate calibration methods applied to biomedical analysisEscandar, Graciela MonicaDamiani, Patricia CeciliaGoicoechea, Hector CasimiroOlivieri, Alejandro CesarBIOMEDICAL ANALYSISFIRST- AND HIGHER-ORDER DATAMULTIVARIATE CALIBRATION METHODShttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate calibration methods constitute an attractive alternative, even when they are applied to intrinsically unselective spectroscopic or electrochemical signals. First-order (i.e., vectorized) data are conveniently analyzed with classical chemometric tools such as partial least-squares (PLS). Certain analytical problems require more sophisticated models, such as artificial neural networks (ANNs), which are especially able to cope with non-linearities in the data structure. Finally, models based on the acquisition and processing of second- or higher-order data (i.e., matrices or higher dimensional data arrays) present the phenomenon known as "second-order advantage", which permits quantitation of calibrated analytes in the presence of interferents. The latter models show immense potentialities in the field of biomedical analysis. Pertinent literature examples are reviewed.Fil: Escandar, Graciela Monica. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Damiani, Patricia Cecilia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaElsevier Science2006-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/151001Escandar, Graciela Monica; Damiani, Patricia Cecilia; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A review of multivariate calibration methods applied to biomedical analysis; Elsevier Science; Microchemical Journal; 82; 1; 1-2006; 29-420026-265XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0026265X05000846info:eu-repo/semantics/altIdentifier/doi/10.1016/j.microc.2005.07.001info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:39:46Zoai:ri.conicet.gov.ar:11336/151001instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:39:46.33CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A review of multivariate calibration methods applied to biomedical analysis
title A review of multivariate calibration methods applied to biomedical analysis
spellingShingle A review of multivariate calibration methods applied to biomedical analysis
Escandar, Graciela Monica
BIOMEDICAL ANALYSIS
FIRST- AND HIGHER-ORDER DATA
MULTIVARIATE CALIBRATION METHODS
title_short A review of multivariate calibration methods applied to biomedical analysis
title_full A review of multivariate calibration methods applied to biomedical analysis
title_fullStr A review of multivariate calibration methods applied to biomedical analysis
title_full_unstemmed A review of multivariate calibration methods applied to biomedical analysis
title_sort A review of multivariate calibration methods applied to biomedical analysis
dc.creator.none.fl_str_mv Escandar, Graciela Monica
Damiani, Patricia Cecilia
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author Escandar, Graciela Monica
author_facet Escandar, Graciela Monica
Damiani, Patricia Cecilia
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author_role author
author2 Damiani, Patricia Cecilia
Goicoechea, Hector Casimiro
Olivieri, Alejandro Cesar
author2_role author
author
author
dc.subject.none.fl_str_mv BIOMEDICAL ANALYSIS
FIRST- AND HIGHER-ORDER DATA
MULTIVARIATE CALIBRATION METHODS
topic BIOMEDICAL ANALYSIS
FIRST- AND HIGHER-ORDER DATA
MULTIVARIATE CALIBRATION METHODS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate calibration methods constitute an attractive alternative, even when they are applied to intrinsically unselective spectroscopic or electrochemical signals. First-order (i.e., vectorized) data are conveniently analyzed with classical chemometric tools such as partial least-squares (PLS). Certain analytical problems require more sophisticated models, such as artificial neural networks (ANNs), which are especially able to cope with non-linearities in the data structure. Finally, models based on the acquisition and processing of second- or higher-order data (i.e., matrices or higher dimensional data arrays) present the phenomenon known as "second-order advantage", which permits quantitation of calibrated analytes in the presence of interferents. The latter models show immense potentialities in the field of biomedical analysis. Pertinent literature examples are reviewed.
Fil: Escandar, Graciela Monica. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Damiani, Patricia Cecilia. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina
Fil: Olivieri, Alejandro Cesar. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
description The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate calibration methods constitute an attractive alternative, even when they are applied to intrinsically unselective spectroscopic or electrochemical signals. First-order (i.e., vectorized) data are conveniently analyzed with classical chemometric tools such as partial least-squares (PLS). Certain analytical problems require more sophisticated models, such as artificial neural networks (ANNs), which are especially able to cope with non-linearities in the data structure. Finally, models based on the acquisition and processing of second- or higher-order data (i.e., matrices or higher dimensional data arrays) present the phenomenon known as "second-order advantage", which permits quantitation of calibrated analytes in the presence of interferents. The latter models show immense potentialities in the field of biomedical analysis. Pertinent literature examples are reviewed.
publishDate 2006
dc.date.none.fl_str_mv 2006-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/151001
Escandar, Graciela Monica; Damiani, Patricia Cecilia; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A review of multivariate calibration methods applied to biomedical analysis; Elsevier Science; Microchemical Journal; 82; 1; 1-2006; 29-42
0026-265X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/151001
identifier_str_mv Escandar, Graciela Monica; Damiani, Patricia Cecilia; Goicoechea, Hector Casimiro; Olivieri, Alejandro Cesar; A review of multivariate calibration methods applied to biomedical analysis; Elsevier Science; Microchemical Journal; 82; 1; 1-2006; 29-42
0026-265X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0026265X05000846
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.microc.2005.07.001
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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