Spider chart, greenness and whiteness assessment of experimentally designed multivariate models for simultaneous determination of three drugs used as a combinatory antibiotic regimen in critical care units: Comparative study.

In this study, five earth-friendly spectrophotometric methods using multivariate techniques were developed to analyze levofloxacin, linezolid, and meropenem, which are utilized in critical care units as combination therapies. These techniques were used to determine the mentioned medications in laboratory-prepared mixtures, pharmaceutical products and spiked human plasma that had not been separated before handling. These methods were named classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), genetic algorithm partial least squares (GA-PLS), and artificial neural network (ANN). The methods used a five-level, three-factor experimental design to make different concentrations of the antibiotics mentioned (based on how much of them are found in the plasma of critical care patients and their linearity ranges). The approaches used for levofloxacin, linezolid, and meropenem were in the ranges of 3-15, 8-20, and 5-25 µg/mL, respectively. Several analytical tools were used to test the proposed methods' performance. These included the root mean square error of prediction, the root mean square error of cross-validation, percentage recoveries, standard deviations, and correlation coefficients. The outcome was highly satisfactory. The study found that the root mean square errors of prediction for levofloxacin were 0.090, 0.079, 0.065, 0.027, and 0.001 for the CLS, PCR, PLS, GA-PLS, and ANN models, respectively. The corresponding values for linezolid were 0.127, 0.122, 0.108, 0.05, and 0.114, respectively. For meropenem, the values were 0.230, 0.222, 0.179, 0.097, and 0.099 for the same models, respectively. These results indicate that the developed models were highly accurate and precise. This study compared the efficiency of artificial neural networks and classical chemometric models in enhancing spectral data selectivity for quickly identifying three antimicrobials. The results from these five models were subjected to statistical analysis and compared with each other and with the previously published ones. Finally, the whiteness of the methods was assessed by the recently published white analytical chemistry (WAC) RGB 12, and the greenness of the proposed methods was assessed using AGREE, GAPI, NEMI, Raynie and Driver, and eco-scale, which showed that the suggested approaches had the least negative environmental impact. Furthermore, to demonstrate solvent sustainability, a greenness index using a spider chart methodology was employed.

Eco-friendly micellar HPLC approach for simultaneous estimation of combination therapy for hidradenitis suppurativa: Applications to spiked human plasma and different dosage forms.

This study introduces a new method for analyzing rifampicin, moxifloxacin, and metronidazole using a green micellar High Performance Liquid Chromatography-Ultraviolet method in bulk drugs, different commercial formulations, and spiked human plasma. The combined therapy of these three broad-spectrum antibiotics is used to cure refractory hidradenitis suppurativa (HS), an inflammatory condition affecting the skin. The sustainable separation was attained on a reversed-phase C18 Kinetex® column maintained at ambient temperature in less than 5 min. The mobile phase comprises 0.1 M sodium dodecyl sulfate (SDS) in water, pH 3.5, adjusted using o-phosphoric acid, and 10% n-butanol. The flow rate was 1 mL/min, with 10 µL injection volume and UV detection at 230 nm. The impact of three key significant variables, SDS concentration, n-butanol percentage, and the mobile phase pH, on suitability parameters was studied. ICH and FDA guidelines were committed to when validating the technique. The results showed linear calibration graphs with high precision and accuracy, in both pure and spiked plasma. The method is efficient, easy to use, and has a high sample throughput, making it suitable for routine analysis in the quality control department and therapeutic monitoring. It is also evaluated as a green-and-white substitute for traditional reported methods.

A validated eco-friendly HPLC-FLD for analysis of the first approved antiviral remdesivir with other potential add-on therapies for COVID-19 in human plasma and pharmaceuticals.

It is crucial to have a reliable and sensitive method for separating common drugs used in SARS-CoV-2 pneumonia treatment protocols for ongoing treatment and upcoming investigations. This study presents an HPLC-FLD approach to analyze three co-administered medicines - remdesivir (RDV), hydroxychloroquine sulphate (HCQ), and levofloxacin hemihydrate (LVX) - in their pure forms, pharmaceutical preparations, and spiked human plasma. The HPLC-FLD analysis was conducted using a Symmetry® C18 column (100 mm × 4.6 mm ID, 3.5 µm particle size) at 40 °C, with (A) an aqueous mixture of 0.02 M phosphate buffer and 0.2% heptane-1-sulphonic acid sodium solutions (50 : 50) adjusted to pH 3, (B) acetonitrile, and (C) methanol as the mobile phase. The injection volume was 10 µL, and the flow rate was 1.5 mL min-1. The detection was done using a multi-wavelength excitation and emission fluorescence detector, with individual optimization for each drug. The drug separation time was less than 10 minutes, and the method showed sensitive and wide linearity ranges for all medicines, with r2 values of more than 0.999. The impact of the mobile phase pH and flow rate on suitability parameters (retention time and number of theoretical plates) was studied. The method was found to be environmentally friendly based on GAPI and AGREE metrics. The validity of the method was evaluated following ICH and FDA guidelines.