A novel high‐performance liquid chromatography method for the enantioseparation of mirabegron ( R ‐mirabegron), a selective β‐3 adrenergic receptor agonist, using cyclodextrin (CD)‐based chiral stationary phases (CSPs) was developed. Seven different CSPs containing β‐, γ‐, hydroxypropyl‐β‐, sulfobutyl‐β‐, carboxymethyl‐β‐, permethyl‐β‐, and phenylcarbamate‐β‐cyclodextrin were evaluated under both polar organic and reversed‐phase conditions. Only the phenylcarbamate‐β‐cyclodextrin containing the Chiral CD‐Ph column displayed enantiorecognition. Optimization of conditions using a full factorial design led to the determination of the most suitable conditions: a mobile phase composition of 90:10:0.1 methanol:water:diethylamine, a flow rate of 0.8 mL/min, and a column temperature of 40°C with enantiomeric elution order, where the impurity S ‐mirabegron elutes first. Using the optimized conditions, enantioseparation with R _s = 1.9 was achieved within 10 min. The developed method was validated according to current guidelines and successfully applied for the determination of S ‐mirabegron, as a chiral impurity in pharmaceutical formulations. The enantiorecognition mechanism was investigated by molecular docking and thermodynamic analysis. Using molecular modeling, the interactions between CDs and the analyte were analyzed at the molecular level, revealing that mirabegron interacts primarily with the phenylcarbamate groups on the outer surface of the structure. Enthalpy‐controlled enantioseparation was consistently observed across all eluent compositions, regardless of the conditions. The developed and validated method is highly suitable for routine determination of the enantiomeric purity of mirabegron, offering a reliable tool for regulatory compliance.

A New FTIR method was developed and validated to simultaneous determination of Captopril (CAP) and Hydrochlorothiazid (HCTZ) in raw material and pharmaceutical dosage forms. The method includes preparation of solid pellets of hydrochlorothiazide and captopril using KBr and the quantitative determination peaks were chosen after conducting an excipient interference study. Then, the validation method was carried out according to the ICH guidelines. The calibration curve was developed using spectral region from 3115.92-3222.1 cm-1 for HCTZ and 1689.91-1800.73 cm-1 for CAP by plotted the peak height (intensity) for the selected peaks against the concentrations where, there are no overlapping with excipients used in the preparation of tablet dosage form. Captopril and Hydrochlorothiazid were detected in the following linear ranges: (0.4-2% w/w) and (0.4-2% w/w); respectively with excellent coefficeients of determination (R2), 0.9989 and 0.9982. Accuracy was found with excellent mean recovery values (98.0–102.0%). The precision showed RSD% was in a satisfactory range (< 2), evidencing the precision of the developed method. In Conclusion this method was inexpensive, environmental friendly and can be employed for simultaneous estimation of CAP and HCTZ in solid dosage forms.

Enantioseparation in HPLC is a considerable challenge in analytical chemistry, frequently requiring numerous trials with varying experimental conditions to achieve baseline separations. To address this issue, we propose a solution that utilizes consensus modelling based on partial least squares (PLS) regression method together with neural network (NN) algorithms and a graph neural network (GNN) method to predict the retention times of compounds on Lux Cellulose-1 chiral stationary phase under various polar organic mode mobile phases. A homogeneous dataset was collected for the developed machine learning methods, consisting of 535 unique molecules and 1,414 retention time measurements under four polar organic mode conditions (acidic and basic methanol, acidic and basic acetonitrile). The PLS + NN consensus model showed outstanding results in condition-specific predictions, achieving R² values over 0.70 and RMSE values below 0.40 in most cases. Conversely, the GNN model excelled in combined predictions under all conditions, achieving a R² of 0.58 and RMSE_CV of 0.49 during cross-validation, as well as a R² of 0.85 and RMSE_Test of 0.25 on the test set. Our research presents a novel approach for predicting chiral separations, offering an easy-to-use, open-access web tool to the scientific community. The robust GNN model was used to create a web server (https://chiralscreen.com) that enables the prediction of retention times, separation capabilities, and elution orders for various compounds. Furthermore, the software helps determine optimal initial chromatographic conditions for separations.

Many drugs are chiral, and their enantiomers often display distinct pharmacological activities. Accurate determination of enantiomerization kinetics during chromatographic separations is therefore of critical importance. Batman peaks (plateau regions arising between partially resolved enantiomer peaks) carry valuable information about on-column interconversion dynamics. We developed an automated R framework that integrates both the unified equation and a stochastic model to extract kinetic and thermodynamic constants from chromatographic data. The workflow applies robust optimization algorithms to enhance flexibility, accelerate fitting, and improve accuracy relative to manual approaches. Quetiapine chromatograms were analyzed over a wide range of flow rates (0.1mL/minto3.0mL/min) and temperatures (10°C to 40°C). Both the unified equation and the stochastic model produced consistent rate constants, which were in good agreement with values obtained from optical rotation experiments. Notably, the stochastic model remained applicable even under extreme conditions where peaks coalesced. Linearized Eyring-Polányi analysis afforded the determination of thermodynamic parameters. The presented workflow provides a robust, flexible, and customizable platform for determining enantiomerization kinetics from Batman peaks. By combining the unified equation with stochastic modeling, it delivers reliable results across diverse chromatographic conditions. This framework is readily adaptable for routine analysis of dynamic enantiomerization in pharmaceutical and analytical chemistry applications.

With the growing emphasis on environmentally friendly analytical practices, green approaches to chiral separation have become vital for assessing the enantiomeric purity of chiral pharmaceutical agents. This study aimed to develop a green HPLC method for the enantioseparation of crizotinib, a tyrosine kinase inhibitor targeting anaplastic lymphoma kinase. The enantioselective performance of seven polysaccharide‐based chiral stationary phases was systematically evaluated under polar organic conditions. Two chiral stationary phases—Lux Cellulose‐3 and Lux Amylose‐1—were identified as providing excellent enantiorecognition. Using experimental design‐based approaches, we optimized three methods and retained them as final: (i) Lux Cellulose‐3 with a methanolic mobile phase, (ii) Lux Cellulose‐3 with an ethanol–water mobile phase, and (iii) Lux Amylose‐1 with an ethanolic mobile phase. All three methods met ICH criteria: linearity ( r ² ≥ 0.9996), precision (RSD ≤ 2%), and accuracy (~98%–101%), allowing quantification of the 0.02% distomer relative to the active enantiomer. Environmental performance was benchmarked using AGREE, Complex MoGAPI, Eco‐Scale/Modified Eco‐Scale, AMGS, and RGB‐fast. All the developed methods showed superior environmental performance compared to the one method previously reported in the literature. However, it is also evident that applying green solvents does not inherently guarantee a cost‐effective or sustainable approach. Overall, the developed methods provide an analytically robust and environmentally sustainable framework for the enantioseparation of crizotinib.

The separation of three proton pump inhibitors (omeprazole, lansoprazole, and rabeprazole) as exemplified molecules containing chiral sulfoxide groups was investigated in polar organic liquid chromatographic mode on seven different polysaccharide stationary phases (Chiralcel OD and OJ; Chiralpak AD, AS, and IA; Lux Cellulose-2 and -4). Different alcohols, such as methanol, ethanol, 1-propanol, 2-propanol, and their combinations, were used as eluents. After method optimization, semi-preparative enantioseparation was successfully applied for the three proton pump inhibitors to collect the individual enantiomers. A detailed investigation was conducted into elution order reversal, thermodynamic parameters, the effect of eluent mixtures, and the hysteresis of retention time and selectivity. Using Chiralpak AS, containing the amylose tris[(S)-α-methylbenzylcarbamate] chiral selector, the separation of the investigated enantiomers was achieved in all four neat eluents, with methanol providing the best results. In many cases, a reversal of the enantiomer elution order was observed. In addition to chiral-selector-dependent reversal, eluent-dependent reversal was also observed. Notably, even replacing methanol with ethanol altered the enantiomer elution order. Both enthalpy- and entropy-controlled enantioseparation were also observed in several cases; however, temperature-dependent elution order reversal was not. The hysteresis of retention and selectivity was further investigated on amylose-type columns in methanol–2-propanol and methanol–ethanol eluent mixtures. The phenomenon was observed on all amylose columns regardless of the eluent mixtures employed. Hystereticity ratios were calculated and used to compare the hysteresis behaviors of different systems. Multivariate statistical analysis revealed that Chiralpak AS exhibited the most distinct enantioselective behavior among the tested columns, likely due to the absence of a direct connection between the carbamate moiety and the aromatic substituent. The present study aided in understanding the mechanisms leading to enantiomer recognition, which is crucial for developing new chiral stationary phases and chiral HPLC method development in general.