sally Tarek

This study introduces an innovative, environmentally sustainable ultra-performance liquid chromatography (UPLC) method with UV detection for the concurrent quantification of six clinically relevant pharmaceuticals—vardenafil, avanafil, sildenafil, dapoxetine, duloxetine, and tadalafil—frequently employed in the management of erectile dysfunction and premature ejaculation. This study employs quality by design (QbD) concepts to optimize chromatographic settings, assuring good selectivity, precision, and resilience, while conforming to green analytical chemistry standards, in contrast to previously published approaches. A face-centered composite design was utilized to systematically optimize critical parameters, resulting in effective separation using a reversed-phase C18 column, an acetate buffer (pH 3), and a mobile phase composed of buffer and methanol (72.5:27.5, v/v) at a flow rate of 0.5 mL/min. The new approach exhibited significant sensitivity and robustness in pharmaceutical dosage forms and contaminated food samples, especially in identifying illicit sildenafil and tadalafil adulteration in honey-based products. The proposed approach was thoroughly validated in accordance with ICH principles, satisfying analytical performance criteria for linearity, precision, accuracy, and robustness. The method's environmental impact was assessed using AGREE metrics, validating its adherence to green analytical chemistry standards. This approach, characterized by its swift analysis time, low solvent usage, and exceptional separation efficiency, serves as a significant analytical instrument for quality control laboratories, pharmaceutical analysis, and food safety monitoring.

ABSTRACT The implementation of core–shell particles in HPLC has many advantages in analytical methodologies, including enhancement of sensitivity and resolution. Moreover, high flow rates and short analysis times could be used to achieve efficient separations. A sensitive and specific UHPLC–MS/MS method was developed and validated for the simultaneous quantification of apixaban (APX) and rivaroxaban (RVX) in rat plasma. This validated method was designed to investigate the potential pharmacokinetic (PK) interactions between dexamethasone (DEX) and both cited drugs in rat model. Separation and validation were performed utilizing a C18 Poroshell 120EC (50 mm × 4.6 mm, 2.7 µm) column with a mobile phase of methanol:water with 0.1% formic acid (95:5, v/v) eluted in an isocratic mode at 0.3 mL/min flow rate. Liquid–liquid extraction method was employed to extract the cited drugs from rat plasma using diethyl ether:dichloromethane (70:30, v/v). The procedure was carried out utilizing positive ionization and multiple reaction monitoring mode (MRM) for the detection of the drugs and the internal standard, moxifloxacin. The bioanalytical method was validated using US-Food and Drug Administration and European Medicines Agency guidelines in terms of selectivity, linearity, accuracy, precision, recovery, dilution integrity, matrix effect, stability, and carryover. On the basis of the findings of the PK study in rat model, a potential drug–drug interaction was observed between DDI and the cited antithrombotic medications that may lead to a decrease in their plasma concentrations. As a result, these findings can be utilized for further clinical investigation.

Novel univariate and chemometrics-aided UV spectrophotometric methods were tailored to undergo the fundamentals of green and white analytical chemistry for the simultaneous estimation of a ternary mixture of olanzapine (OLA), fluoxetine HCL (FLU), and its toxic impurity 4-(Trifluoromethyl) phenol (FMP) without any prior separation. The dual-wavelength ratio spectrum univariate method was used to determine OLA and FLU in the presence of FMP in the range of (4–20) and (5–50) μg/ml, respectively. In compliance with the International Conference on Harmonization (ICH) standards, the technique was validated and established Remarkable accuracy (98–102%) and precision (< 2%) with limits of quantification (LOQs) of 0.432 and 2.002 μg/ml, respectively. Partial least squares (PLS) and artificial neural networks (ANNs) are chemometric methodologies that have advantages over the univariate method and use significant innovations employing Latin hypercube sampling (LHS), allowing the generation of a reliable validation set to guarantee the effectiveness and sustainability of these models. The concentration ranges used were (2–20), (2–20), and (5–50) μg/ml; for PLS, the LOQs were 0.602, 0.508, and 1.429 μg/ml, and the root mean square errors of prediction (RMSEPs) were 0.087, 0.048, and 0.159 for OLA, FMP, and FLU, respectively; and for ANNs, the LOQs were 0.551, 0.465, and 0.965 μg/ml, with RMSEPs of 0.056, 0.047, and 0.087 for OLA, FMP, and FLU, respectively. The developed methods yield a greener National Environmental Methods Index (NEMI) with an eco-scale assessment (ESA) score of 90 and a complementary Green Analytical Procedure Index (complex GAPI) in quadrants with an analytical greenness metric (AGREE) score of 0.8. The Red‒Green–Blue 12 algorithm (RGB 12) scored 88.9, outperforming on reported methods and demonstrating widespread practical and environmental approval. Statistical analysis revealed no noteworthy differences (P > 0.05) among the proposed and published techniques. Both pure powders and pharmaceutical capsules were analyzed via these methods.