Green-assisted spectrophotometric techniques utilizing mathematical and ratio spectra manipulations to resolve severely overlapped spectra of a cardiovascular pharmaceutical mixture.

Cardiovascular diseases, in particular hypertension and hypercholesterolemia, are two of the main causes of death worldwide. These conditions are silent killer syndromes that need a variety of pharmacological treatments to be effectively controlled. This study introduces novel, environmentally friendly spectrophotometric techniques for the simultaneous determination of telmisartan (TMS) and rosuvastatin calcium (RVS) in their pharmaceutical dosage forms. For the simultaneous determination of the binary mixture, the suggested methods included the dual wavelength method (DWM) which utilizes mainly the absorbance difference at 233 nm and 253 for TMS determination and, the absorbance difference at 274 nm and 310 for RVS determination as the selected wavelengths for each drug is directly proportional to the drug of interest independent on the other interfering component. The Fourier-self deconvolutions method (FSDM) depends on compressing their bandwidth to resolve the overlap. Ratio difference spectrophotometric method (RDSM) that utilizes TMS 35 µg.mL-1 and RVS 20 µg.mL-1, respectively as divisors to produce the ratio spectra for each drug. Further manipulation of the produced ratio spectra was applied for the determination of the two drugs. Mean centering method (MCM) where a suitable wavelength range was chosen to exclusively use the informative portions and prevent experimental spectrum noises. The investigated methods showed good levels of detection and quantification together with excellent linearity. The suggested methods' greenness was evaluated using two different greenness evaluation tools, which showed that the methods were green in terms of several factors, including the safety of the chemicals, instruments, and waste. The validity of the methodologieswas investigated by resolving prepared laboratory mixtureswith varying TMS and RVS ratios. The standard addition method also assured the newly added methods. Finally, statistical analysis using the reported method did not reveal any appreciable differences in terms of accuracy and precision. The developed methods can be employed in quality control laboratories to ascertain the binary mixture due to their high precision and affordability.

Green Chemometric Determination of Cefotaxime Sodium in the Presence of Its Degradation Impurities Using Different Multivariate Data Processing Tools; GAPI and AGREE Greenness Evaluation.

Four eco-friendly, cost-effective, and fast stability-indicating UV-VIS spectrophotometric methods were validated for cefotaxime sodium (CFX) determination either in the presence of its acidic or alkaline degradation products. The applied methods used multivariate chemometry, namely, classical least square (CLS), principal component regression (PCR), partial least square (PLS), and genetic algorithm-partial least square (GA-PLS), to resolve the analytes' spectral overlap. The spectral zone for the studied mixtures was within the range from 220 to 320 nm at a 1 nm interval. The selected region showed severe overlap in the UV spectra of cefotaxime sodium and its acidic or alkaline degradation products. Seventeen mixtures were used for the models' construction, and eight were used as an external validation set. For the PLS and GA-PLS models, a number of latent factors were determined as a pre-step before the models' construction and found to be three for the (CFX/acidic degradants) mixture and two for the (CFX/alkaline degradants) mixture. For GA-PLS, spectral points were minimized to around 45% of the PLS models. The root mean square errors of prediction were found to be (0.19, 0.29, 0.47, and 0.20) for the (CFX/acidic degradants) mixture and (0.21, 0.21, 0.21, and 0.22) for the (CFX/alkaline degradants) mixture for CLS, PCR, PLS, and GA-PLS, respectively, indicating the excellent accuracy and precision of the developed models. The linear concentration range was studied within 12-20 µg mL-1 for CFX in both mixtures. The validity of the developed models was also judged using other different calculated tools such as root mean square error of cross validation, percentage recoveries, standard deviations, and correlation coefficients, which indicated excellent results. The developed methods were also applied to the determination of cefotaxime sodium in marketed vials, with satisfactory results. The results were statistically compared to the reported method, revealing no significant differences. Furthermore, the greenness profiles of the proposed methods were assessed using the GAPI and AGREE metrics.

Microscale thermophoresis as a powerful growing analytical technique for the investigation of biomolecular interaction and the determination of binding parameters.

Thein vitropanel of technologies to address biomolecular interactions are in play, however microscale thermophoresis is continuously increasing in use to represent a key player in this arena. This review highlights the usefulness of microscale thermophoresis in the determination of molecular and biomolecular affinity interactions. This work reviews the literature from January 2016 to January 2022 about microscale thermophoresis. It gives a summarized overview about both the state-of the art and the development in the field of microscale thermophoresis. The principle of microscale thermophoresis is also described supported with self-created illustrations. Moreover, some recent advances are mentioned that showing application of the technique in investigating biomolecular interactions in different fields. Finally, advantages as well as drawbacks of the technique in comparison with other competing techniques are summarized.

Analytical Performance and Greenness Evaluation of Five Multi-Level Design Models Utilized for Impurity Profiling of Favipiravir, a Promising COVID-19 Antiviral Drug.

In 2018, the discovery of carcinogenic nitrosamine process related impurities (PRIs) in a group of widely used drugs led to the recall and complete withdrawal of several medications that were consumed for a long time, unaware of the presence of these genotoxic PRIs. Since then, PRIs that arise during the manufacturing process of the active pharmaceutical ingredients (APIs), together with their degradation impurities, have gained the attention of analytical chemistry researchers. In 2020, favipiravir (FVR) was found to have an effective antiviral activity against the SARS-COVID-19 virus. Therefore, it was included in the COVID-19 treatment protocols and was consequently globally manufactured at large-scales during the pandemic. There is information indigence about FVR impurity profiling, and until now, no method has been reported for the simultaneous determination of FVR together with its PRIs. In this study, five advanced multi-level design models were developed and validated for the simultaneous determination of FVR and two PRIs, namely; (6-chloro-3-hydroxypyrazine-2-carboxamide) and (3,6-dichloro-pyrazine-2-carbonitrile). The five developed models were classical least square (CLS), principal component regression (PCR), partial least squares (PLS), genetic algorithm-partial least squares (GA-PLS), and artificial neural networks (ANN). Five concentration levels of each compound, chosen according to the linearity range of the target analytes, were used to construct a five-level, three-factor chemometric design, giving rise to twenty-five mixtures. The models resolved the strong spectral overlap in the UV-spectra of the FVR and its PRIs. The PCR and PLS models exhibited the best performances, while PLS proved the highest sensitivity relative to the other models.

Two Green Micellar HPLC and Mathematically Assisted UV Spectroscopic Methods for the Simultaneous Determination of Molnupiravir and Favipiravir as a Novel Combined COVID-19 Antiviral Regimen.

Following the spread of the COVID-19 pandemic crisis, a race was initiated to find a successful regimen for postinfections. Among those trials, a recent study declared the efficacy of an antiviral combination of favipiravir (FAV) and molnupiravir (MLP). The combined regimen helped in a successful 60% eradication of the SARS-CoV-2 virus from the lungs of studied hamster models. Moreover, it prevented viral transmission to cohosted sentinels. Because both medications are orally bioavailable, the coformulation of FAV and MLP can be predicted. The developed study is aimed at developing new green and simple methods for the simultaneous determination of FAV and MLP and then at their application in the study of their dissolution behavior if coformulated together. A green micellar HPLC method was validated using an RP-C18 core-shell column (5 µm, 150 × 4.6 mm) and an isocratic mixed micellar mobile phase composed of 0.1 M SDS, 0.01 M Brij-35, and 0.02 M monobasic potassium phosphate mixture and adjusted to pH 3.1 at 1.0 mL min-1 flow rate. The analytes were detected at 230 nm. The run time was less than five minutes under the optimized chromatographic conditions. Four other multivariate chemometric model methods were developed and validated, namely, classical least square (CLS), principal component regression (PCR), partial least squares (PLS-1), and genetic algorithm-partial least squares (GA-PLS-1). The developed models succeeded in resolving the great similarity and overlapping in the FAV and MLP UV spectra unlike the traditional univariate methods. All methods were organic solvent-free, did not require extraction or derivatization steps, and were applied for the construction of the simultaneous dissolution profile for FAV tablets and MLP capsules. The methods revealed that the amount of the simultaneously released cited drugs increases up until reaching a plateau after 15 and 20 min for FAV and MLP, respectively. The greenness was assessed on GAPI and found to be in harmony with green analytical chemistry concepts.

Different approaches for the assessment of greenness of spectrophotometric methodologies utilized for resolving the spectral overlap of newly approved binary hypoglycemic pharmaceutical mixture.

Simultaneous measurement of saxagliptin hydrochloride (SAG) and dapagliflozin propanediol monohydrate (DAG) in bulk powder, laboratory-prepared mixtures, and pharmaceutical dosage form were applied by utilizing three precise and sensitive spectrophotometric techniques which were developed and validated. The first method was the induced dual-wavelength approach (IDW), which relied primarily on the use of alternative equality factors (F) to abolish the effect of DAG when determining SAG and vice versa. The ratio difference method (RDM) was the second method, which used 25 µg/ml of DAG and 20 µg/ml of SAG as divisors to determine the amplitude difference on the ratio spectrum of SAG and DAG, respectively. SAG was determined at λmax 221 nm after plateau subtraction followed by multiplication by the divisor of DAG 25 µg/ml using the third method, ratio subtraction coupled with extended ratio subtraction method (RSER). Subsequently, using an extension ratio subtraction of the spectra, DAG was determined at λmax 225 nm was determined. The developed methods were effectively used to estimate SAG and DAG in laboratory-prepared mixtures and pharmaceutical dosage forms, with satisfactory recoveries. The methodologies were assessed for their environmental friendliness using the analytical eco-scale, analytical GREEnness calculator, and green analytical procedureindex (GAPI). These methodologies were validated following the International Conference on Harmonisation (ICH) requirements. A statistical comparison of the obtained findings to those of the published method revealed no significant differences in precision and accuracy. Because of their high precision and cost-effectiveness, the developed methods can be used in quality control laboratories to determine the binary mixture.