Mobile phase systemic solvent optimization

In the development of a SE-HPLC method the variables that may be manipulated and optimized are the column (matrix type, particle and pore size, and physical dimension), buffer system (type and ionic strength), pH, and solubility additives (e.g., organic solvents, detergents). Once a column and mobile phase system have been selected the system parameters of protein load (amount of material and volume) and flow rate should also be optimized. A beneficial approach to the development of a SE-HPLC method is to optimize the multiple variables by the use of statistical experimental design. Also, information about the physical and chemical properties such as pH or ionic strength, solubility, and especially conditions that promote aggregation can be applied to the development of a SE-HPLC assay. Typical problems encountered during the development of a SE-HPLC assay are protein insolubility and column stationary phase... 

Countercurrent chromatography utilizes a pair of immiscible solvent phases which have been preequilibrated in a separatory funnel One phase is used as the stationary phase and the other as the mobile phase. A solvent system composed of 12.5% or 16.0% (w/w) PEG 1000 and 12.5% (w/w) potassium phosphate was usually used for the type XL and XLL cross-axis CPCs. These solutions form two layers the upper layer is rich in PEG and the lower layer is rich in potassium phosphate. The ratio of monobasic to dibasic potassium phosphates determines the pH of the solvent system this effect can be used for optimizing the partition coefficient of proteins. 

Numerous mobile phases (development solvents) are available for lipid work (see Table 1). They often consist of solvent mixtures that vary in polarity, along with small amounts of salts or acids. Because a mixed solvent system allows for an undefined gradient in solvent composition during movement on the silica gel layer, samples with varying polarity can be developed on a single plate in TLC the velocity of the solvent movement is reduced as the solvent front nears the top of the plate optimal separation is obtained with bands or spots with Revalues between 0.1 and 0.6 (63). 

The PRISMA model is a system for the optimization of two- to five-eomponent mobile phases, developed by Nyiredy et al. to simplify the optimization proeess in different planar and column chromatographic systems [66]. This model for the seleetion of solvents and optimization of the mobile phase was developed first for TEC and high-performanee liquid ehromatography (HPLC) [38,67]. 

On the basis of Snyder s system for characterization of solvents the PRISMA method for mobile phase optimization has been developed. This system enables the optimization of solvent strength and mobile phase selectivity and also the transfer of the optimized mobile phase to different planar chromatographic techniques, in our case the PLC. 

Procedures used vary from trial-and-error methods to more sophisticated approaches including the window diagram, the simplex method, the PRISMA method, chemometric method, or computer-assisted methods. Many of these procedures were originally developed for HPLC and were apphed to TLC with appropriate changes in methodology. In the majority of the procedures, a set of solvents is selected as components of the mobile phase and one of the mentioned procedures is then used to optimize their relative proportions. Chemometric methods make possible to choose the minimum number of chromatographic systems needed to perform the best separation. 

Forced-flow development enables the mobile phase velocity to be optimized without regard to the deficiencies of a capillary controlled flow system [34,35). In rotational planar chromatography, centrifugal force, generated by spinning the sorbent layer about a central axis, is used to drive the solvent... 

The PRISMA model was developed by Nyiredy for solvent optimization in TLC and HPLC [142,168-171]. The PRISMA model consists of three parts the selection of the chromatographic system, optimization of the selected mobile phases, and the selection of the development method. Since silica is the most widely used stationary phase in TLC, the optimization procedure always starts with this phase, although the method is equally applicable to all chemically bonded phases in the normal or reversed-phase mode. For the selection of suitable solvents the first experiments are carried out on TLC plates in unsaturated... 

Owing to the instability of silica gel based columns at pH values <2.0 or >8.0, mobile phases must have a pH range of 2.1-7.5. Within this range, a large number of solvent systems have been described. Solvent systems are selected on the basis of several criteria optimal resolution, volatility, LTV transparency, biocompatibility, selectivity, viscosity, and cost. 

Coenegracht et al. [3] have introduced a four solvent system to compose mobile phases for the separation of the parent alkaloids in different medicinal dry plant materials, like Cinchona bark and Opium. Through the use of mixture designs and response surface modeling an optimal mobile phase was found for each type of plant material. These new mobile phases resulted in equally good or better separations than obtained by the procedures of the Pharmacopeias. Although separations were as predicted, the accuracy of the quantitative predictions needed to be improved. 

There are several systems which can be used to select the solvents of the mobile phase. The number of selected solvents and the solvents which are selected not only depend on the chromatographic problem but also on the method which will be used to optimize the system. With response surface methodology it is appropriate to use a minimum number of solvents. For reasons stated below this minimum number of solvents was four. The second question is, which solvents will be selected, is more difficult to answer when a small number of solvents is used because the consequences of a wrong selection are large. Several approaches are possible to select the solvents. The most simple method is comparison with common solvent systems for the solutes under investigation. A more general approach is to use the selectivity triangle of Snyder [4] in the selection of the solvents. 

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