Multivariate analysis to applied in the identification of antidepressants. Part II: principal components analysis (PCA) and soft independent modeling of class analogies (SIMCA)

Authors

  • Janusa Goelzer Sabin Universidade de Santa Cruz do Sul; Departamento de Informática; Grupo de Sistemas e Processos Industriais
  • Marco Flôres Ferrão Universidade de Santa Cruz do Sul; Departamento de Informática; Grupo de Sistemas e Processos Industriais
  • João Carlos Furtado Universidade de Santa Cruz do Sul; Departamento de Informática; Grupo de Sistemas e Processos Industriais

DOI:

https://doi.org/10.1590/S1516-93322004000300015

Keywords:

Antidepressants, Difuse Reflection, Infrared, PCA, SIMCA, Chemometrics

Abstract

In this work the certification of two different drugs used as antidepressants was studied, using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), together with the analysis of principal components (PCA) and the method of soft independent modeling of class analogies (SIMCA). The DRIFT spectra of samples with different concentrations of the active principles amitriptiline and imipramine hydrochlorides had been collected in Magna 550 spectrofotometer, two spectra for each sample, with resolution of 4 cm-1 and 32 scans. The PCA confirmed the existence of two distinct groups, corresponding to the two different active principles used. Otherwise the method of classification SIMCA made possible the recognition of samples of the principles amitriptyline and imipramine hydrochlorides with results indicating 100% of correct classification.

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Published

2004-09-01

Issue

Section

Original Papers

How to Cite

Multivariate analysis to applied in the identification of antidepressants. Part II: principal components analysis (PCA) and soft independent modeling of class analogies (SIMCA). (2004). Revista Brasileira De Ciências Farmacêuticas, 40(3), 387-396. https://doi.org/10.1590/S1516-93322004000300015