A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | |
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=S0103-50532012000800021 |
Resumo: | In this work, near infrared (NIR) imaging spectroscopy was employed in the study of the distribution of the active pharmaceutical ingredient (API) spironolactone and its excipients in tablets. Analyses were performed using 50 µm spatial resolution to analyze 16 mm² of each standard tablet. Interval partial least squares models were used for API and excipients quantification in every pixel in order to obtain concentration maps for each compound. It was obtained errors of quantification between 0.49 and 1.26% when performed the cross-validation using spectral average of each tablet. These calibration models were used to predict individual concentration of each compound in the tablet, in every pixel. The average concentration of all pixels, for each compound yield errors, was between 0.05 and 1.06%. These results indicate that the models were able to quantify all compounds in each pixel. This approach is necessary since it is not possible to know the real concentration of each compound in the pixels. |
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Journal of the Brazilian Chemical Society (Online) |
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A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tabletsimage spectroscopynear infraredspironolactonecontent uniformityIn this work, near infrared (NIR) imaging spectroscopy was employed in the study of the distribution of the active pharmaceutical ingredient (API) spironolactone and its excipients in tablets. Analyses were performed using 50 µm spatial resolution to analyze 16 mm² of each standard tablet. Interval partial least squares models were used for API and excipients quantification in every pixel in order to obtain concentration maps for each compound. It was obtained errors of quantification between 0.49 and 1.26% when performed the cross-validation using spectral average of each tablet. These calibration models were used to predict individual concentration of each compound in the tablet, in every pixel. The average concentration of all pixels, for each compound yield errors, was between 0.05 and 1.06%. These results indicate that the models were able to quantify all compounds in each pixel. This approach is necessary since it is not possible to know the real concentration of each compound in the pixels.Sociedade Brasileira de Química2012-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532012000800021Journal of the Brazilian Chemical Society v.23 n.8 2012reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.1590/S0103-50532012005000022info:eu-repo/semantics/openAccessCarneiro,Renato L.Poppi,Ronei J.eng2012-09-14T00:00:00Zoai:scielo:S0103-50532012000800021Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2012-09-14T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
title |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
spellingShingle |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets Carneiro,Renato L. image spectroscopy near infrared spironolactone content uniformity |
title_short |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
title_full |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
title_fullStr |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
title_full_unstemmed |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
title_sort |
A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets |
author |
Carneiro,Renato L. |
author_facet |
Carneiro,Renato L. Poppi,Ronei J. |
author_role |
author |
author2 |
Poppi,Ronei J. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Carneiro,Renato L. Poppi,Ronei J. |
dc.subject.por.fl_str_mv |
image spectroscopy near infrared spironolactone content uniformity |
topic |
image spectroscopy near infrared spironolactone content uniformity |
description |
In this work, near infrared (NIR) imaging spectroscopy was employed in the study of the distribution of the active pharmaceutical ingredient (API) spironolactone and its excipients in tablets. Analyses were performed using 50 µm spatial resolution to analyze 16 mm² of each standard tablet. Interval partial least squares models were used for API and excipients quantification in every pixel in order to obtain concentration maps for each compound. It was obtained errors of quantification between 0.49 and 1.26% when performed the cross-validation using spectral average of each tablet. These calibration models were used to predict individual concentration of each compound in the tablet, in every pixel. The average concentration of all pixels, for each compound yield errors, was between 0.05 and 1.06%. These results indicate that the models were able to quantify all compounds in each pixel. This approach is necessary since it is not possible to know the real concentration of each compound in the pixels. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-08-01 |
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=S0103-50532012000800021 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532012000800021 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-50532012005000022 |
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.23 n.8 2012 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 |
_version_ |
1750318174063034368 |