Application of micellar liquid chromatography to the simultaneous determination of cardiovascular drugs in biological fluids

Abstract

The application of MLC for simultaneous analysis of cardiovascular drugs in plasma samples was studied and compared with a RP-HPLC method. Both methods were developed and validated according to FDA guidelines. A simple isocratic HPLC-UV method for simultaneous quantification of 6 drugs (used in combination therapy protocols in cardiovascular disorders) in spiked human plasma was reported. Carvedilol, losartan, diltiazem, furosemide, hydrochlorothiazide and propranolol were separated under an isocratic condition of acetonitrile/iso-propanol/15 mM phosphate buffer (pH 2.0) (32.5/2.5/65 v/v/v) mobile phase. The sample preparation consisted of a protein precipitation procedure using a mixture of acetonitrile and zinc sulphate solution prior to injection of sample to the chromatographic system. Method showed acceptable precision, accuracy and linearity. The method was robust and reproducible and the mean recoveries were in the range 99.0-104.4 %.A micellar liquid chromatography coupled with ultraviolet and fluorimetric detectors (MLC-UV-FL) was developed to the simultaneous analysis of furosemide, carvedilol, losartan, diltiazem and propranolol. The developed method was applied to the separation of furosemide, metoprolol and verapamil in human plasma. The whole analysis time for the sample preparation and drug separation was 25 minutes (12 minutes sample preparation and 13 minutes drug separation). All drugs possessed linear behavior (r>0.999 for calibration curves) in their therapeutic concentrations. The mean drug recoveries were 101.9, 100.1 and 100.2% respectively for furosemide, metoprolol and verapamil. The results showed that the MLC is applicable for simultaneous analysis of cardiovascular drugs in biologic samples. An extension to the Jouyban-Acree model was proposed to calculate the retention factor (k) of analytes in HPLC with hydro-organic modifier mixtures as mobile phase by using the Abraham solvent coefficients and Abraham solute parameters. Then the proposed model was extended to calculate the k of different analytes with respect to the nature of analyte, organic modifier, its concentration and type of the stationary phase. The accuracy of the proposed method was evaluated by calculating mean percentage deviation (MPD) as accuracy criterion. The predicted vs. observed plots were also provided as goodness of fit criteria. The developed model prediction capability compared with a number of previous models. The proposed method provided acceptable predictions with the advantage of modeling the effects of organic modifiers, mobile phase compositions, columns and analytes using a single equation. The accuracy of developed model was checked using the one column and one analyte out cross validation analyses and the results showed that the developed model was able to predict the unknown analyte retention and the analytes retentions on unknown column accurately.