Chromatographers are always interested in higher efficiency. This is motivated by the resolution equation, which shows that increases in column efficiency always result in improved resolution. Chromatographic efficiency is affected by a large number of experimental variables and its optimization can be achieved in many different ways, depending upon how many variables one is willing to adjust. These include pressure, temperature, particle size, column length, and eluent velocity. In the early days of high performance liquid chromatography (HPLC), the selection of column formats (particle size, type, and column diameters) was rather limited and thus, optimization often was done by adjusting operational variables such as eluent velocity, column temperature, and operating pressure. Nowadays the selection of column formats is substantially wider and one can find a number of particle sizes between 1.7 μm and 5 μm, and numerous column lengths are achievable by coupling columns in series. This makes optimization of these nominally "discrete" variables possible (that is, particle size and column length).
Optimization of performance (meaning efficiency versus time) in HPLC has been studied for decades. Van Deemter was clearly among the first who understood how plate count on a given column could be optimized by varying the eluent velocity (1). When column length is also allowed to vary, one can use the Poppe plot (2) or kinetic plot (3,4) techniques that consider pressure and time constraints as part of the optimization process. Ultimately, one also can vary particle size, and this optimization has been studied by several LC pioneers including Halasz (5), Knox (6), Horvath (7), and Guiochon (8). We recently summarized these distinct optimization schemes and emphasized the different chromatographic results that these approaches entail (9). The purpose of this column is to propose a simple, stepwise optimization procedure that is solidly founded and to demonstrate its practical utility by applying it to the development of an ultrafast isocratic separation for pharmaceutical applications.
As the march toward more-efficient separations continues, so does the demand for faster separations without sacrificing efficiency. This has been stimulated by the present and persistent need to deal with more and more samples in the same or less time. Clearly "fast" means different things in different applications. For example, "fast" can be a 10-min separation for organic impurities analysis in pharmaceuticals, or it can be a 1-min separation for cleaning analysis in drug manufacturing. In this column, we focus on the implementation of fast LC in pharmaceutical drug product dissolution testing. In such a test, one is primarily interested in quantifying the active pharmaceutical ingredient (API) released from dosage forms, thus, only moderate plate counts are required; here, analysis speed is more important than higher efficiency. Dissolution samples often are analyzed by two techniques, direct UV or HPLC–UV, in almost equal proportions as shown by an online survey of dissolution studies (10). Table I compares these two techniques. A thorough review of the use of HPLC in dissolution studies can be found in a chapter written by Wang and Gray (11). While UV–vis spectroscopy is cheaper and simpler, HPLC offers many advantages, such as better specificity and a greater linear dynamic range. HPLC is also more versatile especially for early drug development when different formulations and strengths are screened. The main disadvantage of traditional HPLC is its relatively slower speed (about 3–5 times slower than UV analysis). Clearly, increasing the speed of HPLC makes it more attractive in this context.