A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles

Autores
Maggio, Ruben Mariano; Castellano, Patricia Margarita; Kaufman, Teodoro Saul
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new approach for testing batch "similarity" through comparison of drug dissolution profiles, based on principal component analysis with the establishment of a confidence region (PCA-CR), is presented. The dissolution curves corresponding to three brands each of Furosemide and Acetaminophen tablets, taken as model drugs, were prepared by dissolution measurements at multiple pre-specified time points. Reference and test data were simultaneously subjected to PCA and pairwise comparisons between the dissolution characteristics of lots of the same and different brands were carried out. The comparisons involved plotting the weighed scores of the first two principal components of reference and test lots, while decision about "similarity" was made by checking for inclusion of more than 80% of the tablets of the test lot in the 95% confidence ellipse of the reference samples. Two published datasets were also analyzed in the same fashion and all the results were compared with information provided by the difference (f1) and similarity (f2) factor tests. Unlike the f2 criterion, the proposed method reflects variability within the individual dissolution curves, being also highly sensitive to profile (shape and size) variations. Comparison between the area enclosed by the confidence ellipses of the weighed scores plot and the region obtained from the bootstrap-calculated acceptable values of the corresponding f2 tests suggested that PCA-CR represents, in general, a more discriminating standard.
Fil: Maggio, Ruben Mariano. 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: Castellano, Patricia Margarita. 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: Kaufman, Teodoro Saul. 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
ACETAMINOPHEN
DISSOLUTION PROFILES
FUROSEMIDE
MULTIVARIATE METHOD
PRINCIPAL COMPONENT ANALYSIS
SIMILARITY TEST
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/136928
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/136928
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A new principal component analysis-based approach for testing "similarity" of drug dissolution profilesMaggio, Ruben MarianoCastellano, Patricia MargaritaKaufman, Teodoro SaulACETAMINOPHENDISSOLUTION PROFILESFUROSEMIDEMULTIVARIATE METHODPRINCIPAL COMPONENT ANALYSISSIMILARITY TESThttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1A new approach for testing batch "similarity" through comparison of drug dissolution profiles, based on principal component analysis with the establishment of a confidence region (PCA-CR), is presented. The dissolution curves corresponding to three brands each of Furosemide and Acetaminophen tablets, taken as model drugs, were prepared by dissolution measurements at multiple pre-specified time points. Reference and test data were simultaneously subjected to PCA and pairwise comparisons between the dissolution characteristics of lots of the same and different brands were carried out. The comparisons involved plotting the weighed scores of the first two principal components of reference and test lots, while decision about "similarity" was made by checking for inclusion of more than 80% of the tablets of the test lot in the 95% confidence ellipse of the reference samples. Two published datasets were also analyzed in the same fashion and all the results were compared with information provided by the difference (f1) and similarity (f2) factor tests. Unlike the f2 criterion, the proposed method reflects variability within the individual dissolution curves, being also highly sensitive to profile (shape and size) variations. Comparison between the area enclosed by the confidence ellipses of the weighed scores plot and the region obtained from the bootstrap-calculated acceptable values of the corresponding f2 tests suggested that PCA-CR represents, in general, a more discriminating standard.Fil: Maggio, Ruben Mariano. 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: Castellano, Patricia Margarita. 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: Kaufman, Teodoro Saul. 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 Science2008-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/136928Maggio, Ruben Mariano; Castellano, Patricia Margarita; Kaufman, Teodoro Saul; A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles; Elsevier Science; European Journal of Pharmaceutical Sciences; 34; 1; 5-2008; 66-770928-0987CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0928098708000602?via%3Dihubinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ejps.2008.02.009info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:10:20Zoai:ri.conicet.gov.ar:11336/136928instacron: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:34982025-10-15 15:10:20.785CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
title A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
spellingShingle A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
Maggio, Ruben Mariano
ACETAMINOPHEN
DISSOLUTION PROFILES
FUROSEMIDE
MULTIVARIATE METHOD
PRINCIPAL COMPONENT ANALYSIS
SIMILARITY TEST
title_short A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
title_full A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
title_fullStr A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
title_full_unstemmed A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
title_sort A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles
dc.creator.none.fl_str_mv Maggio, Ruben Mariano
Castellano, Patricia Margarita
Kaufman, Teodoro Saul
author Maggio, Ruben Mariano
author_facet Maggio, Ruben Mariano
Castellano, Patricia Margarita
Kaufman, Teodoro Saul
author_role author
author2 Castellano, Patricia Margarita
Kaufman, Teodoro Saul
author2_role author
author
dc.subject.none.fl_str_mv ACETAMINOPHEN
DISSOLUTION PROFILES
FUROSEMIDE
MULTIVARIATE METHOD
PRINCIPAL COMPONENT ANALYSIS
SIMILARITY TEST
topic ACETAMINOPHEN
DISSOLUTION PROFILES
FUROSEMIDE
MULTIVARIATE METHOD
PRINCIPAL COMPONENT ANALYSIS
SIMILARITY TEST
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A new approach for testing batch "similarity" through comparison of drug dissolution profiles, based on principal component analysis with the establishment of a confidence region (PCA-CR), is presented. The dissolution curves corresponding to three brands each of Furosemide and Acetaminophen tablets, taken as model drugs, were prepared by dissolution measurements at multiple pre-specified time points. Reference and test data were simultaneously subjected to PCA and pairwise comparisons between the dissolution characteristics of lots of the same and different brands were carried out. The comparisons involved plotting the weighed scores of the first two principal components of reference and test lots, while decision about "similarity" was made by checking for inclusion of more than 80% of the tablets of the test lot in the 95% confidence ellipse of the reference samples. Two published datasets were also analyzed in the same fashion and all the results were compared with information provided by the difference (f1) and similarity (f2) factor tests. Unlike the f2 criterion, the proposed method reflects variability within the individual dissolution curves, being also highly sensitive to profile (shape and size) variations. Comparison between the area enclosed by the confidence ellipses of the weighed scores plot and the region obtained from the bootstrap-calculated acceptable values of the corresponding f2 tests suggested that PCA-CR represents, in general, a more discriminating standard.
Fil: Maggio, Ruben Mariano. 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: Castellano, Patricia Margarita. 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: Kaufman, Teodoro Saul. 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 A new approach for testing batch "similarity" through comparison of drug dissolution profiles, based on principal component analysis with the establishment of a confidence region (PCA-CR), is presented. The dissolution curves corresponding to three brands each of Furosemide and Acetaminophen tablets, taken as model drugs, were prepared by dissolution measurements at multiple pre-specified time points. Reference and test data were simultaneously subjected to PCA and pairwise comparisons between the dissolution characteristics of lots of the same and different brands were carried out. The comparisons involved plotting the weighed scores of the first two principal components of reference and test lots, while decision about "similarity" was made by checking for inclusion of more than 80% of the tablets of the test lot in the 95% confidence ellipse of the reference samples. Two published datasets were also analyzed in the same fashion and all the results were compared with information provided by the difference (f1) and similarity (f2) factor tests. Unlike the f2 criterion, the proposed method reflects variability within the individual dissolution curves, being also highly sensitive to profile (shape and size) variations. Comparison between the area enclosed by the confidence ellipses of the weighed scores plot and the region obtained from the bootstrap-calculated acceptable values of the corresponding f2 tests suggested that PCA-CR represents, in general, a more discriminating standard.
publishDate 2008
dc.date.none.fl_str_mv 2008-05
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/11336/136928
Maggio, Ruben Mariano; Castellano, Patricia Margarita; Kaufman, Teodoro Saul; A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles; Elsevier Science; European Journal of Pharmaceutical Sciences; 34; 1; 5-2008; 66-77
0928-0987
CONICET Digital
CONICET
url http://hdl.handle.net/11336/136928
identifier_str_mv Maggio, Ruben Mariano; Castellano, Patricia Margarita; Kaufman, Teodoro Saul; A new principal component analysis-based approach for testing "similarity" of drug dissolution profiles; Elsevier Science; European Journal of Pharmaceutical Sciences; 34; 1; 5-2008; 66-77
0928-0987
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/S0928098708000602?via%3Dihub
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ejps.2008.02.009
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv 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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score 13.22299

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