Electrochemical Determination of Non-Steroidal Anti-Inflammatory Drugs

Investigation of eco-friendly fluorescence quenching probes for assessment of acemetacin using silver nanoparticles and acriflavine reagent

The non-steroidal anti-inflammatory medication acemetacin was assessed via two straightforward green spectrofluorimetric techniques. The quenching-dependent derivatizing spectrofluorimetric reactions are the master point of this study. Acriflavine-based method (Method I) depends on forming an ion association complex between acriflavine and the drug in a ratio of 1:1, decreasing the former's fluorescence intensity. Acriflavine or Ag NP's intensity-related quenching action goes linearly with the acemetacin concentration in the 2.0-20.0 µg/mL and 1.0-16.0 µg/mL ranges, respectively. The second quenching mechanism depends on using the silver nanoparticles (Ag NP's) as a fluorescence probe (Method II); Ag NP's were prepared from reducing silver nitrate using sodium borohydride. Both methods could be applied to determine pure and pharmaceutical dosage forms of acemetacin. The methods proved valid according to the international conference on harmonization (ICH) guidelines. In addition to this, this work has been estimated under green criteria assessment tools. There is no significant difference between the proposed and the comparison methods after the statistical interpretation.

Simultaneous Voltammetric Determination of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Using a Modified Carbon Paste Electrode and Chemometrics

This work presents the simultaneous quantification of four non-steroidal anti-inflammatory drugs (NSAIDs), paracetamol, diclofenac, naproxen, and aspirin, in mixture solutions, by a laboratory-made working electrode based on carbon paste modified with multi-wall carbon nanotubes (MWCNT-CPE) and Differential Pulse Voltammetry (DPV). Preliminary electrochemical analysis was performed using cyclic voltammetry, and the sensor morphology was studied by scanning electronic microscopy and electrochemical impedance spectroscopy. The sample set ranging from 0.5 to 80 µmol L^-1 was prepared using a complete factorial design (3⁴) and considering some interferent species such as ascorbic acid, glucose, and sodium dodecyl sulfate to build the response model and an external randomly subset of samples within the experimental domain. A data compression strategy based on discrete wavelet transform was applied to handle voltammograms' complexity and high dimensionality. Afterward, Partial Least Square Regression (PLS) and Artificial Neural Networks (ANN) predicted the drug concentrations in the mixtures. PLS-adjusted models (n = 12) successfully predicted the concentration of paracetamol and diclofenac, achieving correlation values of R ≥ 0.9 (testing set). Meanwhile, the ANN model (four layers) obtained good prediction results, exhibiting R ≥ 0.968 for the four analyzed drugs (testing stage). Thus, an MWCNT-CPE electrode can be successfully used as a potential sensor for voltammetric determination and NSAID analysis.

A simple and green LC method for the determination of ibuprofen in milk-containing simulated gastrointestinal media for monitoring the dissolution studies of three dimensional-printed formulations

A fast and green ultra high-performance LC method was developed for the determination of ibuprofen in milk-containing simulated gastrointestinal media to monitor the dissolution of three-dimensional printed formulations. To remove interfering compounds, protein precipitation using methanol as a precipitation reagent was performed. The separation of the target analyte was performed on an C18 column using a mobile phase consisting of 0.05% v/v aqueous phosphoric acid solution: methanol, 25:75% v/v. Method validation was conducted using the total error concept. The β-expectation tolerance intervals did not exceed the acceptance criteria of ± 15%, meaning that 95% of future results will be included in the defined bias limits. The relative bias ranged between ─ 1.1 to + 3.2% for all analytes, while the relative standard deviation values for repeatability and intermediate precision were less than 2.8% and 3.9%, respectively. The achieved limit of detection was 0.01 μg mL^-1 and the lower limit of quantitation was established as 2 μg mL^-1 . The proposed method was simple, and it required reduced organic solvent consumption following the requirements of Green Analytical Chemistry. The method was successfully employed for the determination of ibuprofen in real biorelevant media obtained from dissolution studies. This article is protected by copyright. All rights reserved.