Optimization by experimental design and artificial neural networks of the ion-interaction reversed-phase liquid chromatographic separation of twenty cosmetic preservatives.
Particular attention are recently receiving antimicrobial agents added as preservatives in hygiene and cosmetics commercial products, since some of them are suspected to be harmful to the human health. The preservatives used belong to different classes of chemical species and are generally used in their mixtures. Multi-component methods able to simultaneously determinate species with different chemical structure are therefore highly required in quality control analysis. This paper presents an ion interaction RP-HPLC method for the simultaneous separation of the 20 typical antimicrobial agents most used in cosmetics and hygiene products, that are: benzoic acid, salicylic acid, 4-hydroxybenzoic acid, methyl-, ethyl-, propyl-, butyl-, benzyl-benzoate, methyl-, ethyl-, propyl-, butyl-, benzyl-paraben, o-phenyl-phenol, 4-chloro-m-cresol, triclocarban, dehydroacetic acid, bronopol, sodium pyrithione and chlorhexidine. For the development of the method and the optimization of the chromatographic conditions, an experimental design was planned and models were built by the use of artificial neural network to correlate the retention time of each analyte to the variables and their interactions. The neuronal models developed showed good predictive ability and were used, by a grid search algorithm, to optimize the chromatographic conditions for the separation of the mixture.
Marengo
E
E
Dipartimento di Scienze e Tecnologie Avanzate, Università del Piemonte Orientale Amedeo Avogadro, Spain Marengo 33, 15100 Alessandria, Italy. marengo@unipmn.it
Gianotti
V
V
Angioi
S
S
Gennaro
M C
MC
D002851:Chromatography, High Pressure Liquid / Q000379:methods*; D003358:Cosmetics; D007477:Ions; D016571:Neural Networks, Computer
D003358:Cosmetics; D007477:Ions