Enantiomeric separation of verapamil and its active metabolite, norverapamil, and simultaneous quantification in human plasma by LC-ESI-MS-MS

Correlating physico-chemical properties of analytes with Hansen solubility parameters of solvents using machine learning algorithm for predicting suitable extraction solvent

Artificial neural networks (ANNs) are biologically inspired algorithms designed to simulate the way in which the human brain processes information. In sample preparation for bioanalysis, liquid-liquid extraction (LLE) represents an important step with the extraction solvent selection is the key laborious step. In the current work, a robust and reliable ANNs model for LLE solvent prediction was generated which could predict the suitable solvent for analyte extraction. The developed ANNs model takes a set of chosen descriptors for the cited analyte as an input and predicts the corresponding Hansen solubility parameters of the suitable extraction solvent as a model output. Then, from the solvent combination's appendix, the analyst can identify the proposed extraction solvents' combination for the cited analyte easily and efficiently. For the experimental validation of the model prediction capabilities, twenty structurally diverse drugs belonging to different pharmacological classes were extracted from human plasma. The extraction process was performed using the predicted extraction solvent combination for each drug and quantitively estimated by HPLC/UV methods to assess their extraction recovery. The developed LLE solvent prediction model is in- line with the global trend towards green chemistry since it limits the consumption of organic solvents.

Development and Validation of a Chiral Liquid Chromatographic Assay for Enantiomeric Separation and Quantification of Verapamil in Rat Plasma: Stereoselective Pharmacokinetic Application

A novel, fast and sensitive enantioselective HPLC assay with a new core-shell isopropyl carbamate cyclofructan 6 (superficially porous particle, SPP) chiral column (LarihcShell-P, LSP) was developed and validated for the enantiomeric separation and quantification of verapamil (VER) in rat plasma. The polar organic mobile phase composed of acetonitrile/methanol/trifluoroacetic acid/triethylamine (98:2:0.05: 0.025, v/v/v/v) and a flow rate of 0.5 mL/min was applied. Fluorescence detection set at excitation/emission wavelengths 280/313 nm was used and the whole analysis process was within 3.5 min, which is 10-fold lower than the previous reported HPLC methods in the literature. Propranolol was selected as the internal standard. The S-(-)- and R-(+)-VER enantiomers with the IS were extracted from rat plasma by utilizing Waters Oasis HLB C18 solid phase extraction cartridges without interference from endogenous compounds. The developed assay was validated following the US-FDA guidelines over the concentration range of 1-450 ng/mL (r2 ≥ 0.997) for each enantiomer (plasma) and the lower limit of quantification was 1 ng/mL for both isomers. The intra- and inter-day precisions were not more than 11.6% and the recoveries of S-(-)- and R-(+)-VER at all quality control levels ranged from 92.3% to 98.2%. The developed approach was successfully applied to the stereoselective pharmacokinetic study of VER enantiomers after oral administration of 10 mg/kg racemic VER to Wistar rats. It was found that S-(-)-VER established higher Cmax and area under the concentration-time curve (AUC) values than the R-(+)-enantiomer. The newly developed approach is the first chiral HPLC for the enantiomeric separation and quantification of verapamil utilizing a core-shell isopropyl carbamate cyclofructan 6 chiral column in rat plasma within 3.5 min after solid phase extraction (SPE).