A general systematic approach is described for the chemometric modelling of liquid-liquid extraction data of drugs from biological fluids. Extraction solvents were selected from Snyder's solvent selectivity triangle: methyl tert.-butyl ether, methylene chloride and chloroform. The composition of a mixture of the three extraction solvents was varied and the extraction yield (recovery) of a group of tricyclic amines was measured at all compositions selected. Two process variables, the extraction time and the extraction intensity, were varied simultaneously with the mixture variables to study their influence and their interaction with the mixture composition. The combined mixture and factorial design statistical techniques obtained in this way enabled the recovery to be modelled as a function of both the composition of the extraction liquid and the process variables. The models were assessed with regard to both descriptive and predictive capacities. The results showed that structurally related compounds may demonstrate different partitioning behaviour with regard to both mixture variables and process variables. It was concluded that mixtures of solvents result in higher extraction efficiencies for the amines. A positive effect on the extraction efficiency was demonstrated by the extraction intensity process variable and extraction time. A positive effect on the extraction efficiency was demonstrated by an interaction between extraction intensity and time. Mixture models in which process variables were introduced were recognized as being very suitable for modelling liquid-liquid extraction systems.
Antidepressive Agents, Tricyclic Chromatography, High Pressure Liquid