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A sensitive and selective liquid chromatographic-mass spectrometric method is built to determine oxymatrine in human plasma. After a liquid-liquid extraction for samples, samples are analyzed on a C18 column interfaced with a mass spectrometer. Positive electrospray ionization is employed as the ionization source. The mobile phase is methanol-water containing 10 mmol/L ammonium acetate (60:40) at the flow rate of 0.8 mL/min. The method is linear in the concentration range of 10-1000 ng/mL. The lower limit of quantitation is 10 ng/mL. The intra- and inter-day relative standard deviation across three validation runs over the entire concentration range is less than 14.27%. The accuracy determined at three concentrations (20, 100, and 500 ng/mL for oxymatrine) is within +/- 10.0% in terms of relative error. The method herein described is successfully applied to the evaluation of pharmacokinetic profiles of oxymatrine tablets pills in 18 healthy volunteers. The results show AUC, Tmax, Cmax, and T1/2 between the testing formulation and reference formulation have no significant difference (P > 0.05). Relative bioavailability is 104.2 +/- 13.8%.

Aim: To apply stochastic resonance algorithm (SRA) to quantitative analysis of weak chromatographic signal, which was embedded in the noise., Methods: Based on the theory of stochastic resonance (SR), a simple and effective SRA has been established to improve analytical detection limits of chromatographic analysis, which apply to enhance the signal to noise ratio by the optimization of the parameters and Runge-Kutta method, was established. The method was used to quantitative analysis of phenazopyridine in human plasma by HPLC/UV. Meanwhile this method is compared with HPLC/MS., Results: By experimental chromatographic data sets, an excellent quantitative relationship between concentrations of phenazopyridine and their responses had been obtained. The concentration of phenazopyridine in plasma determined by HPLC/UV with SRA and HPLC/MS showed that there was no significant difference (P > 0.05) between the two methods., Conclusion: The new method was feasible.

Aim: To establish expert system to recommend solvent strength in RP-HPLC by using FAM (fuzzy associate memorizer) networks., Methods: Symbolic rules reflecting the quantitative relationship among molecular structure, capacity factors and solvent strength in RP-HPLC were extracted from trained radial basis function networks. Then FAM networks consisting of these rules were built to recommend mobile phase strength for RP-HPLC., Results: The validation results of the system by monocomponent and mutilcomponent drug samples were satisfied., Conclusion: The mobile phase recommendation system for RP-HPLC analysis of drugs showed reliable performance.

Molecular similarity method was applied to the study of quantitative structure-retention relationship (QSRR) for reversed-phase high performance liquid chromatography (RP-HPLC) analysis of drugs. Based on a thorough and systematic study on the molecular structures of 162 drugs, molecular similarity method, which transformed molecular structure parameters to similarity variables, combined with artificial neural network for the study of QSRR for RP-HPLC. The good relationship module reflecting molecular structure, solvent strength and capacity factor was established. Molecular similarity method was successfully used to predict capacity factors (k') and the validation results of 7 drugs were satisfactory. The correlation coefficient of test samples was 0.996, and the residual standard error was 0.244(n = 18). The correlation coefficient of validation samples was 0.992, and the residual standard error was 0.131(n = 7). The application of molecular similarity method in the study of QSRR for RP-HPLC of drugs is satisfactory.