Multivariate spectral calibration technique based on regression analysis for the quantitative multiresolution of a...

Multivariate spectral calibration techniques based on regression analysis were established for the quantitative multiresolution of a ternary mixture containing parecetamol (PAR) ascorbic acid (AA) and acetylsalicylic acid (ASP) having closely overlapping spectra. The mathematical algorithms of multivariate spectral calibrations as namely tri-linear regression calibration (TLRC) and multi-linear regression calibration (MLRC) are based on the use of the linear regression equations at a three-wavelength set and a ten-wavelength set in the range of 215-305 nm. These calibration techniques do not require any chemical pre-treatment and a graphical procedure of the overlapping spectra. The mathematical content of TLRC and MLRC approaches were briefly formulated for the quantitative analysis of three- or multi-component mixtures. The applicability of the formulated calibration models were tested by analysing the various synthetic ternary mixtures consisting of these active compounds and then these models were applied to real pharmaceutical formulations. It was observed that TLRC and MLRC models give a successful quantitative multiresolution. The experimental results of these techniques were compared with each other as well as with those obtained by literature methods.