Optimization of Preparative Chromatography

The nonlinear nature of preparative chromatography complicates the separation process so much that the derivation of general conclusions regarding either the scaling up or the optimization is a rather difficult task. The optimization of preparative chromatography is further complicated by the fact that the choice of the objective functions in preparative chromatography is not as simple as in... 

The optimization of preparative and even micropreparative chromatography depends on the choice of an appropriate chromatographic system (adsorbent and eluent), sample application and development mode to ensure high purity, and yield of desirable compounds isolated from the layer. For the so-called difficult separations, it is necessary to perform rechromatography by using a system with a different selectivity. But it should be taken into account that achievement of satisfactory results frequently depends on a compromise between yield and the purity of the mixture component that is being isolated. 

Minimum Variance Purity Control of Preparative Chromatography with Simultaneous Optimization of Yield An On-Line Species-Specific Detector... 

Clearly it is not possible to describe every technique, or variation in a particular mode of chromatography, so this chapter will concentrate on the most dominant approaches to optimization of preparative HPLC. The objective here is to maximize the column load and to minimize mobile phase wastage allowing the purification of the largest amount of target in the minimum space. 

Gallant, S., Vunnum, S., and Cramer, S. M. (1996). Optimization of preparative ion-exchange chromatography of proteins-linear gradient separations. /. Chromatogr. 725, 295-314. 

In this section a short overview is given of preparative chromatography and the determination of adsorption isotherm parameters - single and competitive - to be used for computer-assisted optimization of separations. 

It would be very attractive to derive analytical expressions for the optimum experimental conditions from the solution of a realistic model of chromatography, i.e., the equiUbriiun-dispersive model, or one of the lumped kinetic models. Approaches using analytical solutions have the major advantage of providing general conclusions. Accordingly, the use of such solutions requires a minimum number of experimental investigations, first to validate them, then to acquire the data needed for their application to the solution of practical problems. Unfortunately, as we have shown in the previous chapters, these models have no analytical solutions. The systematic use of these numerical solutions in the optimization of preparative separations will be discussed in the next section. 

The above two optimization approaches have different effects on the cost of preparative chromatography. Efficiency is increased by decreasing the particle diameter of the stationary phase. However, then the costs of the phase rapidly increase, along with the costs of the equipment, which needs to be more pressure-stable for operation with smaller particle diameters. It is, therefore, worth looking for systems with optimized selectivities. 

The success of preparative chromatography is strongly related to the way the analytical separation is optimized. As for analytical applications, a resolution of about 1.5-2 is considered to be satisfactory however, optimization of preparative separations is more difficult due to non-linear effects under overloading conditions and some specific aspects that are discussed below. 

The parameters of preparative chromatography that can be adjusted by the chromatographer for optimization are listed in Table 16. Other parameters cannot be modified by the user but are rather related to the nature of the chromatography medium. When an optimization routine does not yield the expected results, it is best to switch to another medium, based on either a different mass transfer principle or another matrix material. The adsorption process that occurs at a chromatography surface is very complex and is poorly understood. This is especially true for non-specific adsorption. This is why it is necessary to carry out the optimization with the real solutions. Experiments with artificial samples often do not result in conditions that can be transferred to the real situation. The most important targets for optimization are purity and productivity. After the required purity has been achieved, the productivity can be optimized. Productivity includes costs, column size, and operation time. It also includes the lifetime of the column material. 

HPLC of Biological Macromolecules Second Edition, Revised and Expanded, edited by Karen M. Gooding and Fred E. Regnier Scale-Up and Optimization in Preparative Chromatography Principles and Biopharmaceutical Applications, edited by Anurag S. Rathore and AJoy Velayudhan... 

The scale of preparative chromatography is larger than that of conventional analytical chromatography. Therefore, a practical starting point is to develop an analytical separation that optimizes the isolation conditions. Optimization of the analytical method implies seeking conditions which combine maximum resolution of the peak of interest and minimum elution time, under the restriction of a limited pressure drop. " The optimized conditions determine the column, mobile... 

There are many advantages of the SMB technology compared to batch preparative chromatography. The process is continuous and the solvent requirement is minimal compared to batch. In SMB, the whole stationary phase is used for the separation while in batch chromatography only a small part of the column is involved in the separation. This allows optimization of productivity with respect to the stationary phase. 

Investigators dealing with optimization of chromatography systems for preparative separation on laboratory or larger scales in the first stage using TLC selected stationary and mobile phases to obtain a resolution Rj > 1.5 for each pair of touching bands. Such a resolution permits the introduction of a 3 mg/g adsorbent. 

Golshan-Shirazi, S. and Guiochon, G., Theory of optimization of the experimental conditions of preparative liquid chromatography optimization of column efficiency, Anal. Chem., 61, 1368, 1989. 

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