Multi-Criteria Decision Making to the Optimization of Reversed-Phase Liquid Chromatographic Separation of Six Anticonvulsant Agents in Serum: A Study with Potential for Use in Patient Drug Level Monitoring

Abstract

The chemometrics approach was applied for the simultaneous optimization of separation quality and analysis time of six anticonvulsant agents in RP-HPLC. The effect of two experimental parameters was studied on retention by means of multivariate analysis. The factors considered were the organic modifier concentration and pH in the mobile phase. The experiments were performed according to a response surface experimental design. Then Pareto-Optimality method, an approach from multi-criteria decision making, was employed. The obtained regression models were characterized by both descriptive and predictive ability. After statistical evaluation, optimum conditions as well as quantitative values were shown and discussed.

Keywords:

• Anticonvulsant agents
• Chemometric methods
• Experimental design
• High performance liquid chromatography
• Multi-criteria decision making
• Optimization

Notes

^a C_m = Organic modifier concentration (%); pH of mobile phase.

R, correlation coefficient; F, Fisher ratio; S.E., standard error of the estimate; , cross-validated correlation coefficient; the numbers in parenthesis are mean effect.

*The amount of compounds as mentioned on the control serums' label (µg/ml).

**The amount of compounds measured according to calibration curves in this study (µg/ml).

^a The number in parenthesis is the mean of concentration range.