Nerissa L. Denola

Development of retention prediction models for adrenoreceptor agonists and antagonists on a polyvinyl alcohol‐bonded stationary phase in hydrophilic interaction chromatography

Retention prediction models based on multiple linear regression (MLR) and artificial neural network (ANN) for adrenoreceptor agonists and antagonists chromatographed on a polyvinyl alcohol-bonded stationary phase under hydrophilic interaction chromatography were described. The models showed the combined effects of solute structure and mobile phase composition on the retention behavior of the analytes. Using stepwise MLR, the retentions of the studied compounds were satisfactorily described by a five-predictor model; the predictors being the %ACN, the logarithm of the partition coefficient (log D), the number of hydrogen bond donors (HBD), the desolvation energy for octanol (FOct), and the total absolute atomic charge (TAAC). The inclusion of the solute-related descriptors suggested that hydrophilic interactions such as hydrogen bonding and also ionic interactions are possible mechanisms by which analytes are retained on the studied system. ANN prediction models were also derived using the predictors derived from MLR as inputs and log k as outputs. The best network architectures were found to be 5-3-1 for the datasets at pH 3.0 and 4.0, and 5-4-1 for the dataset at pH 5.0. The optimized ANNs showed better predictive properties than the MLR models for both training and test sets under all pH conditions.

Multiple linear regression and artificial neural network retention prediction models for ginsenosides on a polyamine-bonded stationary phase in hydrophilic interaction chromatography

The development of retention prediction models for the seven ginsenosides Rf, Rg1, Rd, Re, Rc, Rb2, and Rb1 on a polyamine-bonded stationary phase in hydrophilic interaction chromatography (HILIC) is presented. The models were derived using multiple linear regression (MLR) and artificial neural network (ANN) using the logarithm of the retention factor (log k) as the dependent variable for four temperature conditions (0, 10, 25, and 40 degrees C). Using stepwise MLR, the retention of the analytes in all the temperature conditions was satisfactorily described by a two-predictor model wherein the predictors were the percentage of ACN (%ACN) in the mobile phase and local dipole index (LDI) of the compounds. These predictors account for the contribution of the solute-related variable (LDI) and the influence of the mobile phase composition (%ACN) on the retention behavior of the ginsenosides. A comparison of the models derived from both MLR and ANN revealed that the trained ANNs showed better predictive abilities than the MLR models in all temperature conditions as demonstrated by their higher R(2) values for both training and test sets and lower average percentage deviation of the predicted log k from the observed log k of the test compounds. The ANN models also showed excellent performance when applied to the prediction of the seven ginsenosides in different sample matrices.

Modeling of retention of adrenoreceptor agonists and antagonists on polar stationary phases in hydrophilic interaction chromatography: a review

Retention prediction models for reversed-phase liquid chromatography (RPLC) have been extensively studied owing to the fact that RPLC remains the most widely used chromatographic technique especially in the field of pharmaceutical and biomedical analyses. However, RPLC is not always the method of choice for the analysis of some compounds that have high polarity. Hydrophilic interaction chromatography (HILIC) has been gaining interest in the last few years as an alternative option to RPLC for the analysis of polar and hydrophilic analytes. HILIC is a variant of normal-phase liquid chromatography, but utilizes water in a water-miscible organic solvent as the eluent in conjunction with a hydrophilic stationary phase. The present review aims to summarize recent contributions on the development of retention prediction models for a group of basic analytes, namely, the adrenoreceptor agonists and antagonists, on different polar stationary phases. The use of multiple linear regression and artificial neural networks in model building is highlighted.

Effects of alcohols on CE enantioseparation of basic drugs with native γ-CD as chiral selector

The effects of alcohol on the CE enantioseparation of selected basic drugs with gamma-CD as the chiral selector was investigated. The enantioseparation behavior of the analytes with gamma-CD in the absence and presence of different alcohols specifically methanol, ethanol, 2-propanol (IPA), and 2-methyl-2-propanol (TBA), the relationship of enantiomeric resolution (R(s)) values with either hydrophobicity or bulkiness of the alcohols, as well as the effect of these alcohols on interaction of the analytes with gamma-CD were studied. Results showed that hydrophobicity and/or bulkiness of alcohols have an influence on the enantioresolution of most of the analytes based on the relatively high correlation coefficients (R) obtained between R(s) versus log P and between R(s) versus ovality (i.e., parameter to indicate bulkiness of a molecule). Comparison of the values of the average binding constants obtained for each enantiomeric pair in the presence and absence of 5% IPA showed that alcohols can increase, decrease, or give a minimal effect on the analyte-gamma-CD interaction depending on the analyte. Furthermore, the significant enhancement in the enantioresolution of both propranolol and pindolol in the presence of either IPA or TBA led to the baseline enantioresolution of both drugs using 35 mM gamma-CD.

Sensitive Micellar Electrokinetic Chromatographic Determination of Salbutamol, Guaifenesin, and Dyphylline in Oral Formulations

Abstract A sensitive micellar electrokinetic chromatographic method to analyze salbutamol, guaifenesin, and dyphylline employing 20 µm inner diameter capillaries was developed. Sensitive analysis of the drugs at a concentration range of about 0.5 to 60 µg/mL was demonstrated using large volume sample stacking with 75% acetonitrile as the sample diluent. Using dyphylline as the internal standard, detection limits were 0.07 µg/mL and 0.21 µg/mL for salbutamol and guaifenesin, respectively. Using the standard addition method, accurate determination of salbutamol and guaifenesin in syrup and capsule preparations was achieved. Recovery values were satisfactory (95 to 100%), but matrix interferences affected the reproducibility.

Effect of Counter‐Anions on the Retention of Zwitterionic Quinolones in Reversed‐Phase Liquid Chromatography

Abstract The effects of counter‐anions on the reversed‐phase HPLC retention of zwitterionic quinolones were studied. Four counter‐anions, perchlorate, tetrafluoroborate, trifluoroacetate, and dihydrogenphosphate, were used as mobile phase additives. HPLC analysis was performed at a mobile phase pH 3, to ensure the complete protonation of the piperizine ring and to suppress the ionization of the carboxylic acid groups of the analytes. Results showed that retention factors of all analytes increased to varying degrees with increasing counter‐anion concentration. The increase in retention of the analytes is attributed to the chaotropic effect exhibited by the counter‐anions. Complete separation of all the studied compounds was achieved by varying the type and amount of counter‐anions present in the mobile phase. The changes in selectivity offered by these counter‐anions would be beneficial, especially for developing chromatographic methods for the analysis of quinolones in different sample matrices.