Publication:
Determination of paracetamol and orphenadrine citrate in pharmaceutical tablets by modeling of spectrophotometric data using partial least-squares and artificial neural networks

dc.contributor.authorLawan Sratthaphuten_US
dc.contributor.authorNongluck Ruangwisesen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-08-24T01:40:00Z
dc.date.available2018-08-24T01:40:00Z
dc.date.issued2007-10-01en_US
dc.description.abstractThe estimation of paracetamol and orphenadrine citrate in a multicomponent pharmaceutical dosage form by spectrophotometric method has been reported. Because of highly interference in the spectra and the presence of non-linearity caused by the analyte concentrations which deviate from Beer and Lambert's law, partial least-squares (PLS) and artificial neural networks (ANN) techniques were used for the calibration. A validation set of spiked samples was employed for testing the accuracy and precision of the methods. Reasonably good recoveries were obtained with PLS for paracetamol and the use of an ANN allowed the estimation of orphenadrine citrate, a minor component which could not be adequately modeled by PLS. Three production batches of a commercial sample were analysed, and there was statistically no significant difference (P<0.05) between the results with the proposed method and those obtain with the official comparative method. © 2007 The Pharmaceutical Society of Japan.en_US
dc.identifier.citationYakugaku Zasshi. Vol.127, No.10 (2007), 1723-1729en_US
dc.identifier.doi10.1248/yakushi.127.1723en_US
dc.identifier.issn13475231en_US
dc.identifier.issn00316903en_US
dc.identifier.other2-s2.0-34848904762en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/24105
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34848904762&origin=inwarden_US
dc.subjectBiochemistry, Genetics and Molecular Biologyen_US
dc.titleDetermination of paracetamol and orphenadrine citrate in pharmaceutical tablets by modeling of spectrophotometric data using partial least-squares and artificial neural networksen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=34848904762&origin=inwarden_US

Files

Collections