Development and evaluation of a simple and easy HPLC-UV system simultaneously suitable for determination of 24 anti-epileptic drugs in plasma

Fabrication of a surface molecularly imprinted polymer membrane based on a single template and its application in the separation and extraction of phenytoin, phenobarbital and lamotrigine

An innovative molecularly imprinted polymer membrane (MIPM) was prepared with polyvinylidene difluoride (PVDF) as the support, phenytoin (PHT) as the single template, methacrylic acid as the functional monomer, ethylene glycol dimethacrylate as the cross-linking reagent, azobisisobutyronitrile as the initiator, and acetonitrile-dimethylformamide (1 : 1.5, v/v) as the porogen. These materials were characterized via scanning electron microscopy, Fourier transform infrared spectroscopy, Brunauer-Emmett-Teller measurements and X-ray photoelectron spectroscopy. Their adsorption performances were evaluated through a series of experiments including isothermal adsorption, kinetic adsorption, selective adsorption, adsorption-desorption, reusability, and preparation reproducibility. Additionally, the application was explored by investigating the extraction recovery of MIPMs towards PHT, phenobarbital (PHB) and lamotrigine (LTG) in different matrices including methanol, normal saline (NS), phosphate buffer solution (PBS) and plasma. The results showed that MIPMs with rough and porous surfaces were successfully constructed, which offered good preparation reproducibility, reusability and selectivity. The adsorption capacities of MIPMs towards PHT, PHB and LTG were 2.312, 2.485 and 2.303 mg g-1, respectively, while their corresponding imprinting factors were 8.538, 12.122 and 4.562, respectively. The adsorption equilibrium of MIPMs was achieved within 20 min at room temperature without stirring or ultrasonication. The extraction recoveries of MIPMs for PHT, PHB or LTG in methanol, NS and PBS were more than 80% with an RSD% value of less than 3.64. In the case of plasma, the extraction recovery of MIPMs for PHT and PHB was more than 80% with an RSD% value of less than 2.41, while that of MIPMs for LTG was more than 65% with an RSD% value of less than 0.99. All the results indicated that the preparation method for MIPMs was simple, stable, and reliable, and the prepared MIPMs possessed excellent properties to meet the extraction application of PHT, PHB and LTG in different matrices.

Turbulent Flow Liquid Chromatography-Tandem Mass Spectrometry Methods for Antiepileptic Drug Quantitation in Serum

Epilepsy is characterized by abnormal electrical discharges in the brain that result in unprovoked seizures. Pharmacotherapy with antiepileptic drugs (AED) can help control the incidence of epileptic seizures. AED therapeutic regimens often need to be individually tailored. Therapeutic drug monitoring (TDM) of AED is required to optimize therapeutic efficacy and minimize the risk of any associated destructive toxicities. We describe a turbulent flow liquid chromatography-tandem mass spectrometry (TFC-MS/MS) method for the detection of seven different AED in human serum. TFC-MS/MS testing was performed using a TLX-2 online sample preparation liquid chromatography (SPLC) system coupled to an API 5500 Q-Trap tandem mass spectrometer. Quantification of 10,11-dihydro-10-hydroxycarbamazepine, lacosamide, lamotrigine, levetiracetam, rufinamide, topiramate, and zonisamide was, respectively, performed using calibration curves (2-60 μg/mL, R2 > 0.99) with precisions of <10%.

Simple HPLC-UV Method for Therapeutic Drug Monitoring of 12 Antiepileptic Drugs and Their Main Metabolites in Human Plasma

The objective of the present report was to develop and validate a simple, selective, and reproducible high-performance liquid chromatography method with UV detection suitable for routine therapeutic drug monitoring of the most commonly used antiepileptic drugs and some of their metabolites. Simple precipitation of plasma proteins with acetonitrile was used for sample preparation. 10,11-dihydrocarbamazepine was used as an internal standard. Chromatographic separation of the analytes was achieved by gradient elution on a Phenyl-Hexyl column at 40 °C, using methanol and potassium phosphate buffer (25 mM; pH 5.1) as a mobile phase. The method was validated according to the FDA guidelines for bioanalytical method validation. It showed to be selective, accurate, precise, and linear over the concentration ranges of 1-50 mg/L for phenobarbital, phenytoin, levetiracetam, rufinamide, zonisamide, and lacosamide; 0.5-50 mg/L for lamotrigine, primidone, carbamazepine and 10-monohydroxycarbazepine; 0.2-10 mg/L for carbamazepine metabolites: 10,11-trans-dihydroxy-10,11-dihydrocarbamazepine and carbamazepine-10,11-epoxide; 0.1-10 mg/L for oxcarbazepine; 2-100 mg/L for felbamate and 3-150 mg/L for ethosuximide. The suitability of the validated method for routine therapeutic drug monitoring was confirmed by quantification of the analytes in plasma samples from patients with epilepsy on combination antiepileptic therapy.

Antiepileptic drug concentration detection based on Raman spectroscopy and an improved snake optimization-convolutional neural network algorithm

A method for measurement of antiepileptic drug concentrations based on Raman spectroscopy and an optimization algorithm for mathematical models are proposed and investigated. This study uses Raman spectroscopy to measure mixed antiepileptic drugs, and an Improved Snake Optimization (ISO)-Convolutional Neural Network (CNN) algorithm is proposed. Raman spectroscopy is widely used in the identification of pharmaceutical ingredients due to its sharp peaks, no pre-treatment of samples and non-destructive detection. To analyze the spectral data precisely, a machine learning method is used in this paper. The ISO algorithm is an improved intelligent swarm algorithm in which the method of generating random solutions is improved, which can ensure that a comprehensive local search of the model is performed, the global search capability is maintained at a later stage, and the convergence speed is accelerated. In this study, 360 groups of oxcarbazepine, carbamazepine, and lamotrigine drug mixtures are measured using Raman spectroscopy, and the raw spectral data after pre-processing are trained and evaluated using ISO-CNN algorithms, and the results are compared and analyzed with those obtained from other algorithms such as the Northern Goshawk Optimization algorithm, Chameleon Swarm Algorithm, and White Shark Optimizer algorithm. The results show that the best ISO-CNN algorithm training is achieved for oxcarbazepine, with a determination coefficient and root mean square error of 0.99378 and 0.0295 for the validation set, and 0.99627 and 0.0278 for the test set. The overall results suggest that Raman spectroscopy combined with machine learning algorithms can be a potential tool for drug concentration prediction.

Ecofriendly appraisal of stability-indicating high-performance chromatographic assay of canagliflozin and metformin with their toxic impurities; in silico toxicity prediction

Canagliflozin is an oral hypoglycemic drug recently formulated in combination with a biguanide, metformin hydrochloride, for improving its hypoglycemic action. Canagliflozin has one reported major degradation product, also metformin hydrochloride has one reported major degradation product, cyanoguanidine, and has a potential toxic impurity, melamine, that is reported to cause crystalluria that causes chronic kidney inflammation and nephrolithiasis leading to a renal failure. As per International Conference of Harmonization guidelines; a drug degradation product is classified as a type of drug impurities. Toxicity profiles of canagliflozin and metformin major degradation products were studied where in silico data disclosed toxicity too; the development of a specific chromatographic thin layer chromatographic assay was a must for quantification of such toxic related components along with the drugs in laboratory-prepared mixtures as a superior study. The proposed method was validated as per the International Conference of Harmonization and applied for the assay of Vokanamet tablets. The separation was achieved using acetone:ethyl acetate:acetic acid (8:2:0.2, by volume) as scanning eluted bands at 205 nm. For minimal environmental impact; greenness profile appraisal of the proposed assay was performed by three greenness assessment approaches; analytical Eco-Scale, Green Analytical Procedure Index, and Greenness metric approaches.

A simple and easy non-derivatization gas chromatography-mass spectrometry method for simultaneous quantification of valproic acid, gabapentin, pregabalin, and vigabatrin in human plasma

Immunoassays are currently not available in commercial kits for the quantification of valproic acid, vigabatrin, pregabalin, and gabapentin, which also cannot suffer the limitations of interferences of substances with similar structures. Chromatography is a good alternative to immunoassay. In this study, a simple and robust non-derivatization gas chromatography-mass spectrometry method for simultaneous determination of the above four drugs in human plasma was developed and validated for therapeutic drug monitoring purposes. This method employed benzoic acid as the internal standard with hydrochloric acid for plasma acidification and ACN for precipitate protein. The supernatant was directly injected into gas chromatography-mass spectrometry for analysis. Good linearity was obtained with linear correlation coefficients of the four analytes of 0.9988-0.9996. Extraction recoveries of valproic acid, vigabatrin, pregabalin, and gabapentin were respectively in the ranges of 91.3%-94.5%, 90.0%-90.9%, 90.0%-92.1%, and 88.0%-92.2% with the relative standard deviation values less than 12.6%. Intra- and inter-batch precision and accuracy, and stability assays were all acceptable. Taken together, the novel method developed in this study provided easy plasma pretreatment, good extraction yield, and high chromatographic resolution, which has been successfully validated through the quantification of valproic acid in the plasma of 46 patients with epilepsy.