INVESTIGADORES
SATUF Maria Lucila
artículos
Título:
Complementary use of partial least-squares and artificial neural networks for the non-linear spectrophotometric analysis of pharmaceutical samples
Autor/es:
GOICOECHEA, H. C.; COLLADO, M. S.; SATUF, M. L.; OLIVIERI, A. C.
Revista:
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
Editorial:
Springer-Verlag
Referencias:
Lugar: Heidelberg, Alemania; Año: 2002 vol. 374 p. 460 - 465
ISSN:
1618-2642
Resumen:
The complementary use of partial least-squares (PLS) multivariate calibration and artificial neural networks (ANNs) for the simultaneous spectrophotometric determination of three active components in a pharmaceutical formulation has been explored. The presence of nonlinearities caused by chemical interactions was confirmed by a recently discussed methodology based on Mallows augmented partial residual plots. Ternary mixtures of chlorpheniramine, naphazoline and dexamethasone in a matrix of excipients have been resolved by using PLS for the two major analytes (chlorpheniramine and naphazoline) and ANNs for the minor one (dexamethasone). Notwithstanding the large number of constituents, their high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. No extraction procedures using non-aqueous solvents are required.