Assessment of different PLS algorithms for quantification of three spectrally overlapping drugs


Gergov G., ALIN A., Doychinova M., De Luca M., Simeonov V., Al-Degs Y.

BULGARIAN CHEMICAL COMMUNICATIONS, vol.49, no.2, pp.410-421, 2017 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 49 Issue: 2
  • Publication Date: 2017
  • Journal Name: BULGARIAN CHEMICAL COMMUNICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.410-421
  • Keywords: PLS1 algorithms: NIPALS, SIMPLS, KERNEL, BIDIAGONALIZATION, Spectral overlapping, De Luca method, Bootstrap method, SARIDON formulation, PARTIAL LEAST-SQUARES, SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION, MULTIVARIATE CALIBRATION TECHNIQUES, DATA SETS, LIQUID-CHROMATOGRAPHY, CHEMOMETRIC METHODS, KERNEL ALGORITHM, CROSS-VALIDATION, TERNARY MIXTURES, MATLAB TOOLBOX
  • Dokuz Eylül University Affiliated: Yes

Abstract

The primary aim of the present study was to compare the prediction power of different PLS algorithms as applied to the quantification of three spectrally overlapping drugs. Four variants of PLS were chosen for multivariate calibration and prediction of the three components of the drug formulation (paracetamol, propyphenazone and caffeine). NIPALS and SIMPLS algorithms were the most commonly used algorithms. The other tested algorithms were Kernel and Bidiagonalization which have been rarely applied in pharmaceutical analysis.