Optimization of the HPLC separation conditions for the determination of albendazol and its main metabolites by gradient elution using a 2-dimensional tG-T-DryLab-model is demonstrated. The optimal separation of the compounds of interest from endogenous plasma constituens was obtained by simultaneously optimizing gradient range, temperature and gradient time. DryLab sufficiently resolved the peaks of interest from the endogenous plasma components. The results show excellent comparisons of the DryLab models with the real experiments.

Different C18 columns were used with DryLab for the optimization of temperature and gradient steepness for the separation of impurities from a pharmaceutical product. For this application, each of nine different columns gave similar results (a resolution Rs equal to 2.1-2.7), while a column with an embedded polar group gave somewhat better separation (Rs = 3.2).

Four experimental runs where temperature T and gradient time t_G are varied allow the computer-prediction of reversed-phase liquid chromatographic (RPLC) separation for different combinations of temperature and gradient time. This in turn can provide significant changes in selectivity and a resulting optimization of separation. If this procedure is repeated for different columns, additional control over selectivity and resolution becomes possible. The simultaneous variation of T and t_G for columns from different sources was studied for two samples, as a means of evaluating the general advantage of this approach for RPLC method development. Changes in relative retention with T were found to be approximately constant for different values of t_G and for different RPLC columns; similarly, changes in relative retention with tG were roughly independent of changes in temperature or the column. The latter relationships can be useful in matching ("tracking") peaks between runs during method development based on the present approach, as well as for other applications discussed in here and in Part II.

The separation of samples that contain more than 15 to 20 analytes (n>15–20) is typically difficult and usually requires gradient elution. We have examined the reversed-phase liquid chromatographic separation of 24 samples with 8≤n≤48 as a function of temperature T and gradient time tG. The required peak capacity was determined for each sample, after selecting T and tG for optimum selectivity and maximum sample resolution. Comparison of these results with estimates of the maximum possible peak capacity in reversed-phase gradient elution was used to quantify the maximum value of n for some required sample resolution (when T and tG have been optimized). These results were also compared with literature studies of similar isocratic separations as a function of ternary-solvent mobile phase composition, where the proportions of methanol (MeOH), tetrahydrofuran (THF) and water were varied simultaneously. This in turn provides information on the relative effectiveness of these two different method development procedures (optimization of T and tG vs. % MeOH and % THF) for changing selectivity and achieving maximum resolution.

By optimizing column temperature T and gradient time tG, complex samples can often be separated by means of reversed-phase high-performance liquid chromatography (RP-LC). Conclusions reached in Part I suggest that the complete separation of such samples will be difficult, however, when more than 15–20 components are present in the sample. An alternative approach is to carry out two separations with different conditions (T, tG) in each run. The combination of results from these two runs then allows the total analysis of the sample, providing that every sample component is adequately resolved in one run or the other. Examples of this approach, carried out by means of computer simulation, are shown here for several samples of varying complexity. Also considered is the ability of a single separation where T and tG are optimized to enable the separation and analysis of one or more individual sample components from complex mixtures (e.g., drugs in animal plasma), including the resolution of isomeric compounds from each other.

Previous studies have shown that four experimental runs, where both temperature T and gradient time tG are varied, can be used for the reliable prediction of separation as a function of these two variables (two-dimensional optimization). Computer simulation (e.g., DryLab) can then be used to predict “optimized” conditions for maximum sample resolution using either isocratic or gradient elution. Samples that contain a large number of components (e.g., n>15–20) present a greater challenge. Resolution for these more complex samples is often quite sensitive to small changes in T or tG, in turn requiring greater accuracy in predictions that result from computer simulation. In the present study of several samples, we have examined computer simulation errors that can arise from inexact expressions for retention time as a function of T, tG or isocratic %B. Resulting conclusions are applicable to both complex and simpler samples, in either one- or two-dimensional optimization. Means to anticipate and minimize the impact of these predictive errors are examined.