Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods

Detalhes bibliográficos
Autor(a) principal: Marques-Marinho,Flávia D.
Data de Publicação: 2013
Outros Autores: Reis,Ilka A., Vianna-Soares,Cristina D.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of the Brazilian Chemical Society (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000900011
Resumo: Analytical methods require adequate curve adjusting models to express reliability. The ordinary or weighted least squares methods (OLSM or WLSM, respectively) were used to determine the most adequate mathematical model for the analytical curve, beginning from the simplest method (linear) to quadratic. These models were evaluated with respect to normality and homoscedasticity of the residues. Analytical curves were built by injection of 1, 5, 10, 15 and 20 mL of simvastatin at 40 µg mL-1 (40, 200, 400, 600 and 800 ng) or of 10 mL of simvastatin at 4, 20, 40, 60 and 80 µg mL-1, employing high-performance liquid chromatography with photo-diode array detection (l 238 nm). The best-adjusted models were the linear and the quadratic, when observed in terms of the dataset masses and concentrations, respectively. In the considered range, WLSM was more appropriate than OLSM. The different behavior indicated the need for careful selection of the most adequate model to express the analytical curve and the need for assuring the reliability of the used method.
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spelling Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methodsanalytical curvesHPLC-UVleast squares methodweighted modelsvalidationAnalytical methods require adequate curve adjusting models to express reliability. The ordinary or weighted least squares methods (OLSM or WLSM, respectively) were used to determine the most adequate mathematical model for the analytical curve, beginning from the simplest method (linear) to quadratic. These models were evaluated with respect to normality and homoscedasticity of the residues. Analytical curves were built by injection of 1, 5, 10, 15 and 20 mL of simvastatin at 40 µg mL-1 (40, 200, 400, 600 and 800 ng) or of 10 mL of simvastatin at 4, 20, 40, 60 and 80 µg mL-1, employing high-performance liquid chromatography with photo-diode array detection (l 238 nm). The best-adjusted models were the linear and the quadratic, when observed in terms of the dataset masses and concentrations, respectively. In the considered range, WLSM was more appropriate than OLSM. The different behavior indicated the need for careful selection of the most adequate model to express the analytical curve and the need for assuring the reliability of the used method.Sociedade Brasileira de Química2013-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000900011Journal of the Brazilian Chemical Society v.24 n.9 2013reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.5935/0103-5053.20130187info:eu-repo/semantics/openAccessMarques-Marinho,Flávia D.Reis,Ilka A.Vianna-Soares,Cristina D.eng2013-09-24T00:00:00Zoai:scielo:S0103-50532013000900011Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2013-09-24T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false
dc.title.none.fl_str_mv Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
title Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
spellingShingle Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
Marques-Marinho,Flávia D.
analytical curves
HPLC-UV
least squares method
weighted models
validation
title_short Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
title_full Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
title_fullStr Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
title_full_unstemmed Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
title_sort Construction of analytical curve fit models for simvastatin using ordinary and weighted least squares methods
author Marques-Marinho,Flávia D.
author_facet Marques-Marinho,Flávia D.
Reis,Ilka A.
Vianna-Soares,Cristina D.
author_role author
author2 Reis,Ilka A.
Vianna-Soares,Cristina D.
author2_role author
author
dc.contributor.author.fl_str_mv Marques-Marinho,Flávia D.
Reis,Ilka A.
Vianna-Soares,Cristina D.
dc.subject.por.fl_str_mv analytical curves
HPLC-UV
least squares method
weighted models
validation
topic analytical curves
HPLC-UV
least squares method
weighted models
validation
description Analytical methods require adequate curve adjusting models to express reliability. The ordinary or weighted least squares methods (OLSM or WLSM, respectively) were used to determine the most adequate mathematical model for the analytical curve, beginning from the simplest method (linear) to quadratic. These models were evaluated with respect to normality and homoscedasticity of the residues. Analytical curves were built by injection of 1, 5, 10, 15 and 20 mL of simvastatin at 40 µg mL-1 (40, 200, 400, 600 and 800 ng) or of 10 mL of simvastatin at 4, 20, 40, 60 and 80 µg mL-1, employing high-performance liquid chromatography with photo-diode array detection (l 238 nm). The best-adjusted models were the linear and the quadratic, when observed in terms of the dataset masses and concentrations, respectively. In the considered range, WLSM was more appropriate than OLSM. The different behavior indicated the need for careful selection of the most adequate model to express the analytical curve and the need for assuring the reliability of the used method.
publishDate 2013
dc.date.none.fl_str_mv 2013-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000900011
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532013000900011
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.5935/0103-5053.20130187
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Química
publisher.none.fl_str_mv Sociedade Brasileira de Química
dc.source.none.fl_str_mv Journal of the Brazilian Chemical Society v.24 n.9 2013
reponame:Journal of the Brazilian Chemical Society (Online)
instname:Sociedade Brasileira de Química (SBQ)
instacron:SBQ
instname_str Sociedade Brasileira de Química (SBQ)
instacron_str SBQ
institution SBQ
reponame_str Journal of the Brazilian Chemical Society (Online)
collection Journal of the Brazilian Chemical Society (Online)
repository.name.fl_str_mv Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)
repository.mail.fl_str_mv ||office@jbcs.sbq.org.br
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