Central composite design with the help of multivariate curve resolution in loadability optimization of RP-HPLC to scale-up a binary mixture

Sequential purification of cannabidiol by two-dimensional liquid chromatography combined with modeling and simulation of elution profiles

Cannabidiol (CBD) has garnered significant attention for its neuroprotective properties, and research on its therapeutic effects has increased dramatically in recent years. However, the systematic purification of CBD through scalable processes has remained bottleneck due to the structural similarities of the cannabinoids. Although preparative chromatography is considered as a potential solution, it is usually time-consuming and expensive. Therefore, the development of scalable strategy via fast and accurate optimization approach is crucial. The present study aimed to develop a sequential process for the scalable purification of CBD through an eco-friendly ethanolic extraction using ultrasonic assisted extraction, decarboxylation of cannabidiolic acid optimized by response surface methodology, followed by the development of off-line two-dimensional semi-preparative chromatography, boosted with stacked injection overloading. In the first dimension, a column packed with macroporous resin allows to enrich the target substance and then, the behavior of resin column for scale-up procedure were predicted and optimized by developed mathematical model. A C18 column was used in the second dimension. The CBD purity and recovery obtained were 94.3 and 82.1 %, respectively. A robust and reliable method was employed for CBD enrichment/purification, which can be generalized to other bioactive compounds in complex matrices.

Box-Behnken design aided optimization and validation of developed reverse phase HPLC analytical method for simultaneous quantification of dolutegravir sodium and lamivudine co-loaded in nano-liposomes

A stability-indicating reversed-phase high-performance liquid chromatography method for simultaneous estimation of dolutegravir sodium and lamivudine encapsulated in the nanoliposomal formulation was developed. The chromatographic parameters namely, organic phase ratio, flow rate, and sample injection volume were selected as independent factors and were optimized by multivariate Box-Behnken design. Responses analyzed were retention time, peak area, and resolution. The optimized chromatographic method with Hypersil BDS C8 CN column as stationary phase and methanol and acetonitrile mixture and acidified Milli-Q water (pH 2.8, adjusted with 0.02% v/v orthophosphoric acid) as the mobile phase in an isocratic elution mode was validated according to parameters of International Conference on Harmonization Q1(R2) guidelines. The validated reversed-phase high-performance liquid chromatography method exhibited specificity for both dolutegravir sodium and lamivudine in the presence of degradation products as well as the liposomal matrix. This method was effectively utilized to determine the amount of drug entrapped and drug loading efficiency of dolutegravir sodium and lamivudine in a nano-liposomal formulation.

Recent applications of retention modelling in liquid chromatography

Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention‐mechanism studies, for determining physical parameters, such as lipophilicity, and for various more‐practical purposes, including method development and optimization, method transfer, and stationary‐phase characterization and comparison. The review focusses on the effects of mobile‐phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most‐common models are addressed in detail, i.e. the log‐linear (linear‐solvent‐strength) model, the quadratic model, the log–log (adsorption) model, the mixed‐mode model, and the Neue–Kuss model. Isocratic and gradient‐elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one‐ and two‐dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.