Computer-Assisted Modeling, Prediction, and Multifactor Optimization in Micellar Electrokinetic Chromatography of Ionizable Compounds

Abstract

Previously, the use of phenomenological models to describe the migration behavior of acidic solutes in micellar electrokinetic chromatography (MEKC) was reported. In this paper, the phenomenological approach is further extended by including both acidic and basic solutes and simultaneously taking two important experimental factors (pH and micelle concentration) into consideration. In addition, a general method is described to model the migration behavior of ionizable (both acidic and basic) solutes in MEKC with anionic and cationic micelles. The practical implication of the phenomenological approaches is that they will provide quantitative relationships between solute migration and experimental factors such that the migration behavior can be predicted on the basis of a few initial experiments and that physicochemical parameters of solutes can also be estimated from model fitting. Through computer-assisted modeling, migration behavior of several acidic and basic solutes over a pH-micelle concentration factor space was successfully predicted on the basis of only five experiments. Furthermore, this phenomenological approach was used to predict the separation of a group of aromatic amines in MEKC with anionic micelles, which resulted in a successful separation of 18 aromatic amines in less than 15 min.

MECCSIM, training software for micellar electrokinetic capillary chromatography

“…Here data on the pH dependence of the distribution coefficient as a function of pH are usually not available. A recent publication [10] reported on computerassisted modelling of MECC of ionizable compounds. Distribution coefficients of ionized and non-ionized forms were determined.…”

Retention modeling and resolution optimization for a group ofN‐phenylpyrazole derivatives in micellar electrokinetic chromatography using empirical and physicochemical models

“…In recent years, in order to predict the optimal separation conditions with the minimum number of experiments, several strategies in MEKC have been reported [1,2]. As an example, it can be cited the overlapping resolution mapping (ORM) [3][4][5][6][7][8][9], iterative regression strategies [10], physicochemical approaches [11][12][13][14], empirical equations [15][16][17][18], and artificial neural networks (ANNs) [19]. In order to carry out these studies, several designs can be used, e.g., the Plackett-Burman design [20,21] and the orthogonal array design (OAD) [22] which are factorial designs suitable for screening the influence of many parameters and to monitor possible interactions among a large number of factors, or the central composite design [23,24] that can provide a response surface for the prediction of areas of optimum performance.…”

“…Thus, Khaledi et al [11][12][13][14] introduced physicochemical models describing the migration behavior of both acidic and basic solutes as a function of the separation buffer composition and physicochemical constants. First, a description of migration in terms of pK a , micelle-water binding constant, and mobility of the anionic solutes in the absence of micelles has been performed [11].…”

“…A description of the solute mobility in terms of physical and chemical constants of each solute, the pH of the buffer, and the micelle concentration in the buffer has also been reported [12]. Finally, a model describing the migration of ionizable (acidic and basic) solutes as a function of the simultaneous variation of the pH and micelles concentration has been proposed [13]. Recently, our research team has developed a physicochemical model to predict the retention of neutral compounds as a function of micellized surfactant and the organic modifier concentration [14].…”

Migration behaviour of monovalent weak acids in micellar electrokinetic chromatography mobility model versus retention model

“…Recently, the migration behaviour has been studied extensively and several models have been reported that describe migration in terms of physico-chemical constants, such as micelle binding constants and apparent dissociation constants in micellar media [7][8][9][10][11]. In this work, the mobility and retention models |or monovalent weak acids in an anionic micellar system are evaluated and compared.…”