Simultaneous spectrophotometric quantitative analysis of elbasvir and grazoprevir using assisted chemometric models

Univariate versus multivariate spectrophotometric data analysis of triamterene and xipamide; a quantitative and qualitative greenly profiled comparative study

Triamterene (TRI) and xipamide (XIP) mixture is used as a binary medication of antihypertension which is considered as a major cause of premature death worldwide. The purpose of this research is the quantitative and qualitative analysis of this binary mixture by green univariate and multivariate spectrophotometric methods. Univariate methods were zero order absorption spectra method (D⁰) and Fourier self-deconvolution (FSD), as TRI was directly determined by D⁰ at 367.0 nm in the range (2.00-10.00 µg/mL), where XIP show no interference. While XIP was determined by FSD at 261.0 nm in the range (2.00-8.00 µg/mL), where TRI show zero crossing. Multivariate methods were Partial Least Squares, Principal Component Regression, Artificial Neural Networks, and Multivariate Curve Resolution-Alternating Least Squares. A training set of 25 mixtures with different quantities of the tested components was used to construct and evaluate them, 3 latent variables were displayed using an experimental design. A set of 18 synthetic mixtures with concentrations ranging from (3.00-7.00 µg/mL) for TRI and (2.00-6.00 µg/mL) for XIP, were used to construct the calibration models. A collection of seven synthetic mixtures with various quantities was applied to build the validation models. All the proposed approaches quantitative analyses were evaluated using recoveries as a percentage, root mean square error of prediction, and standard error of prediction. Strong multivariate statistical tools were presented by these models, and they were used to analyze the combined dosage form available on the Egyptian market. The proposed techniques were evaluated in accordance with ICH recommendations, where they are capable of overcoming challenges including spectral overlaps and collinearity. When the suggested approaches and the published one were statistically compared, there was no discernible difference between them. The green analytical method index and eco-scale tools were applied for assessment of the established models greenness. The suggested techniques can be used in product testing laboratories for standard pharmaceutical analysis of the substances being studied.

Green adherent spectrophotometric determination of molnupiravir based on computational calculations; application to a recently FDA-approved pharmaceutical dosage form

Molnupiravir is an oral antiviral drug developed to provide significant benefit in reducing hospitalizations or deaths in mild COVID-19. Integrated green computational spectrophotometric method was developed for the determination of molnupiravir. Theoretical calculations were performed to predict the best coupling agent for efficient diazo coupling of molnupiravir. The binding energy between molnupiravir and various phenolic coupling agents, α-naphthol, β-naphthol, 8-hydroxyquinoline, resorcinol, and phloroglucinol, was measured using Gaussian 03 software based on the density functional theory method and the basis set B3LYP/6-31G(d). The results showed that the interaction between molnupiravir and 8-hydroxyquinoline was higher than that of other phenolic coupling agents. The method described was based on the formation of a red colored chromogen by the diazo coupling of molnupiravir with sodium nitrite in acidic medium to form a diazonium ion coupled with 8-hydroxyquinoline. The absorption spectra showed maximum sharp peaks at 515 nm. The reaction conditions were optimized. Beer's law was followed over the concentration range of 1-12 μg/ml molnupiravir. Job's continuous variation method was developed and the stoichiometric ratio of molnupiravir to 8-hydroxyquinoline was determined to be 1:1. The described method was successfully applied to the determination of molnupiravir in pure form and in pharmaceutical dosage form. The results showed that the proposed method has minimal environmental impact compared to previous HPLC method.

Different spectrophotometric methods for simultaneous determination of lesinurad and allopurinol in the new FDA approved pharmaceutical preparation; additional greenness evaluation

Lesinurad and allopurinol have been formulated in a combined dosage form providing a new challenge for the treatment of gout attacks. Two mathematical based spectrophotometric methods, area under the curve, and artificial neural networks have been developed for simultaneous determination of lesinurad and allopurinol in pure form and in combined pharmaceutical dosage form. Area under the curve has been utilized to resolve the spectral overlap between lesinurad and allopurinol. Values of area under the curve and area absorptivity were measured at two selected wavelength ranges of 242-250 nm and 255-265 nm. Two mathematically constructed equations have been used to determine the concentrations of the drugs under the study. Advanced chemometry based model, artificial neural network, has been developed utilizing the UV spectral data of lesinurad and allopurinol through various defined steps. A five-level, two-factor experimental design was used to construct 25 mixtures. Thirteen mixtures were used to set up the calibration model and 12 mixtures were used to construct a validation set. The artificial neural network model was optimized to enable precise spectrophotometric determination of the drugs under the study. The described mathematically bases spectrophotometric methods have been successfully applied to the determination of lesinurad and allopurinol in the new combined, Duzallo® tablets. Furthermore, the greenness of the described methods was assessed using four different tools namely, the national environmental method index, the analytical eco-scale, the green analytical procedure index and the AGREE evaluation method. The proposed methods showed more adherence to the greenness characters in comparison to the previously reported HPLC method.

Genetic algorithm based artificial neural network and partial least squares regression methods to predict of breakdown voltage for transformer oils samples in power industry using ATR-FTIR spectroscopy

The current study proposes a novel analytical method for calculating the breakdown voltage (BV) of transformer oil samples considered as a significant method to assess the safe operation of power industry. Transformer oil samples can be analyzed using the Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with multivariate calibration methods. The partial least squares regression (PLSR) back propagation-artificial neural network (BP-ANN) methods and a genetic algorithm (GA) for variable selection are used to predict and assess breakdown voltage in transformer oil samples from various Iranian transformer oils. As a result, the root mean square error (RMSE) and correlation coefficient for the training and test sets of oil samples are also calculated. In the GA-PLS-R method, the squared correlation coefficient (R²pred) and root mean square prediction error (RMSEP) are 0.9437 and 2.6835, respectively. GA-BP-ANN, on the other hand, had a lower RMSEP value (0.2874) and a higher R²pred function (0.9891). Considering the complexity of transformer oil samples, the performance of GA-BP-ANN has resulted in an efficient approach for predicting breakdown voltage; consequently, it can be effectively used as a new method for quantitative breakdown voltage analysis of samples to evaluate the health of transformer oil. .

Comparative evaluation of different mathematical models for simultaneous UV spectrophotometric quantitative analysis of velpatasvir and sofosbuvir

Velpatasvir and sofosbuvir are new drugs prescribed in a combined pharmaceutical dosage form that pose a new challenge for the treatment of chronic hepatitis C. In this work, a comparative evaluation of the classical mathematical model, simultaneous equations, and the advanced mathematical model, partial least squares, for the spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in bulk powder and in the new combined pharmaceutical dosage form was presented. The mathematical simultaneous equation method was used to resolve the overlap between velpatasvir and sofosbuvir. The absorbance and absorbativity values at 255 and 244.8 were used to construct two mathematical equations required for spectrophotometric quantitative analysis of the drugs under study. Partial least squares, an advanced mathematical tool dealing with the full spectral data of velpatasvir and sofosbuvir, was also introduced. An experimental design for the calibration sets and validation sets for the binary mixture of the drugs under study were created. The model was optimized based on a five-level, two-factor experimental design. Pre-processing of the spectral data was applied and resulted in the exclusion of the spectral region from 200 to 230 nm due to noise. The described methods were successfully applied to the spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in Epclusa® tablets.

Spectrophotometric Determination of Metformin in Different Pharmaceutical Combinations with Glipizide or Sitagliptin in Presence of Toxic Impurities of Metformin

BACKGROUND

The presented quadruple divisor spectrophotometric method was able to resolve and analyze a complex quintuple drug matrix with severe overlapped spectra without previous separation or extraction steps or need of complicated apparatus like chromatographic methods and had the advantage of being green as the solvent used was water.

METHOD

Simple, sensitive and precise quadruple devisor spectrophotometric method was developed for simultaneous determination of metformin, glipizide, and sitagliptin in presence of metformin potential impurities melamine and cyanoguanidine. The proposed method was applied for analysis of metformin, glipizide, and sitagliptin in pure form and pharmaceutical formulation (tablets). The developed method was validated and met the requirements for ICH guidelines with respect to linearity, accuracy, precision, specificity and robustness.

RESULTS

A linear response was observed in the range of 2-27, 2-20, 1-20, 0.5-10, and 1-10 μg/mL for metformin, glipizide, sitagliptin, melamine and cyanoguanidine, respectively with a correlation coefficient of 0.9996 and 0.9998, 0.9997, 0.9997 and 0.9996 for metformin, glipizide, sitagliptin, melamine and cyanoguanidine, respectively.

CONCLUSION

The validated method was successfully applied for determination of the studied drugs in Janumet® and Engilor® tablets; moreover the results were statistically compared to those obtained by the reported RP-HPLC method and no significant difference was found between them; indicating the ability of proposed method to be used for routine quality control analysis of these drugs.

Application of different spectrofluorimetric approaches for quantitative determination of acetylsalicylic acid and omeprazole in recently approved pharmaceutical preparation and human plasma

Acetylsalicylic acid and omeprazole were recently formulated by the new FDA-approved drug Yosprala ® Tablets. This novel combination was prescribed to reduce the risk of myocardial infarction in patients who were at risk for developing peptic ulcer while taking acetylsalicylic acid. In the current work, two different high precision sensitive fluorescence spectroscopic methods were developed for quantitative analysis of the above drugs in pharmaceutical dosage form and spiked human plasma. Acetylsalicylic acid was quantitatively analyzed due to its unique native fluorescence nature. The fluorescence emission of acetylsalicylic acid was quantitatively determined at 404 nm after excitation at 296 nm without any interference from omeprazole. Omeprazole, which has a free terminal secondary amino group, reacted with 4-chloro-7-nitrobenzo-2-oxa-1, 3-diazole (NBD-Cl) by a nucleophilic substitution mechanism to form a highly fluorescent dark yellow fluorophore. Omeprazole was quantitatively analyzed by measuring the emission fluorescence intensity of the dark yellow fluorophore at 535 nm after excitation at 465 nm. Various parameters affecting the described methods were carefully checked and optimized. The calibration curves were found to be linear over the concentration range of 50-1600 ng/ml for acetylsalicylic and 30-2000 ng/ml for omeprazole. The proposed methods were successfully applied to the quantitative analysis of the two drugs in the pharmaceutical dosage form Yosprala ® and in spiked human plasma.