Novel designed electrochemical sensor for simultaneous determination of linezolid and meropenem pneumonia drugs

Quercetin nanoparticles decorated on Arabic gum and polyvinyl alcohol composite as a film sensor for fluorescence detection of meropenem

Moving towards green chemistry to minimize the diverse effect of chemicals on human health and environment has become a great issue in chemistry. On the other hand, determination of pharmaceuticals is an important issue for both human health and environment. In this regard two natural and benign compounds such as quercetin a polyphenolic flavonoid and Arabic Gum (AG) a polysaccharide were used to construct a sensor for meropenem. Herein, a new method was established for the synthesis of AG and polyvinyl alcohol (PVA) composite decorated by quercetin nanoparticles (QUENPs) as a fluorimetric film sensor to measure meropenem. In order to embed QUENPs in the polymer composite substrate, first QUENPs were synthesized and then added to the prepared composite solution under optimal conditions. The characteristics of AG and PVA composite (AG-PVA) and AG-PVA composite decorated by QUENPs films (QUENPs-AG-PVA), before and after the addition of meropenem was studied by TEM, FT-IR and EDX-Mapping. The developed film sensor was placed in a holder made with 3D printer. The difference in the fluorescence intensity of the fabricated film before and after the addition of meropenem was taken as the signal for measuring meropenem. The effect of different parameters on the fabrication of film fluorimetric sensor such as the concentration of polymer solutions, the volume of QUENPs and the volume of glycerol were investigated. Factors affecting the measurement of meropenem such as pH, type of buffer, volume of meropenem solution added on the sensor and time were also investigated. Under the obtained optimum conditions, the calibration graph was linear in the concentration range of 50-800 ng mL-1 with a correlation coefficient (r) of 0.9976 and the detection limit was 42.6 ng mL-1. The relative standard deviation was 3.5% and 1.4%, for eight replicate determinations of 100 ng mL-1 and 400 ng mL-1 of meropenem, respectively. The proposed method was successfully utilized for determination of meropenem in blood serum, human urine and pharmaceutical samples.

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.

Analytical Methodologies for the Estimation of Oxazolidinone Antibiotics as Key Members of anti-MRSA Arsenal: A Decade in Review

Gram-positive bacterial infections are among the most serious diseases related with high mortality rates and huge healthcare costs especially with the rise of antibiotic-resistant strains that limits treatment options. Thus, development of new antibiotics combating these multi-drug resistant bacteria is crucial. Oxazolidinone antibiotics are the only totally synthetic group of antibiotics that showed activity against multi-drug resistant Gram positive bacteria including MRSA because of their unique mechanism of action in targeting protein synthesis. This group include approved marketed members (tedizolid, linezolid and contezolid) or those under development (delpazlolid, radezolid and sutezolid). Due to the significant impact of this class, larger number of analytical methods were required to meet the needs of both clinical and industrial studies. Analyzing these drugs either alone or with other antimicrobial agents commonly used in ICU, in the presence of pharmaceutical or endogenous biological interferences, or in the presence of matrix impurities as metabolites and degradation products poses a big analytical challenge. This review highlights current analytical approaches published in the last decade (2012-2022) that dealt with the determination of these drugs in different matrices and discusses their advantages and disadvantages. Various techniques have been described for their determination including chromatographic, spectroscopic, capillary electrophoretic and electroanalytical methods. The review comprises six sections (one for each drug) with their related tables that depict critical figures of merit and some experimental conditions for the reviewed methods. Furthermore, future perspectives about the analytical methodologies that can be developed in the near future for determination of these drugs are suggested.

A method to determine two antibiotics prescribed to treat nosocomial infections in plasma and urine by micellar liquid chromatography

Combined prescription of the antimicrobial drugs linezolid and meropenem is a common strategy to treat multidrug-resistant nosocomial infections. We propose an innovative method to determine these two drugs in plasma and urine, based on micellar liquid chromatography. Both biological fluids were diluted in mobile phase, filtered and directly injected, without any extraction step. Using a C18 column and a mobile phase of 0.1 M sodium dodecyl sulfate - 10 % methanol, phosphate buffered at pH 3, running under isocratic mode, both antibiotics were eluted without overlapping in<15 min. Detection was by absorbance: 255 nm for linezolid and 310 nm for meropenem. The influence of sodium dodecyl sulfate and methanol concentration on retention factor was established for both drugs using an interpretative approach assisted by chemometrics. The procedure was successfully validated following the guidelines of 2018 Bioanalytical Method Validation Guidance for Industry in terms of: linearity (determination coefficients over 0.99990), calibration range (1 - 50 mg/L), instrumental and method sensitivity, trueness (bias of -10.8 to + 2.4%), precision (relative standard deviation of < 10.2%), dilution integrity, carry-over effect, robustness and stability. It should be emphasized that the method uses low volumes of toxic and volatile solvents and can be achieved in a short period. The procedure was found useful for routine analysis, as it was cost-affordable, more eco-friendly and safer than hydroorganic HPLC, easy-to-handle and highly sample-throughput. Finally, it was applied to incurred samples of patients taking this medication.

Graphene-based electrochemical sensors for antibiotic detection in water, food and soil: A scientometric analysis in CiteSpace (2011-2021)

The residues of antibiotics in the environment pose a potential health hazard, so highly sensitive detection of antibiotics has always appealed to analytical chemists. With the widespread use of new low-dimensional materials, graphene-modified electrochemical sensors have emerged as an excellent candidate for highly sensitive detection of antibiotics. Graphene, its derivatives and its composites have been used in this field of exploration in the last decade. In this review, we have not only described the field using traditional summaries, but also used bibliometrics to quantify the development of the field. The literature between 2011 and 2021 was included in the analysis. Also, the sensing performance and detection targets of different sensors were compared. We were able to trace not only the flow of research themes, but also the future areas of development. Graphene is a material that has a high potential to be used on a large scale in the preparation of electrochemical sensors. How to design a sensor with selectivity and low cost is the key to bring this material from the laboratory to practical applications.