Complementary use of partial least-squares and artificial neural networks for the non-linear spectrophotometric analysis of pharmaceutical samples View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-10

AUTHORS

Héctor C. Goicoechea, María S. Collado, María L. Satuf, Alejandro C. Olivieri

ABSTRACT

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 non-linearities 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. More... »

PAGES

460-465

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00216-002-1435-3

DOI

http://dx.doi.org/10.1007/s00216-002-1435-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000200853

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/12373395


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