Combining chemometrics and the technique for the order of preference by similarity to ideal solution: A new approach to multiple-response optimization of HPLC compared to desirability function

Oral delivery of posaconazole-loaded phospholipid-based nanoformulation: Preparation and optimization using design of experiments, machine learning, and TOPSIS

Phospholipid-based nanosystems show promising potentials for oral administration of hydrophobic drugs. The study introduced a novel approach to optimize posaconazole-loaded phospholipid-based nanoformulation using the design of experiments, machine learning, and Technique for Order of Preference by Similarity to the Ideal Solution. These approaches were used to investigate the impact of various variables on the encapsulation efficiency (EE), particle size, and polydispersity index (PDI). The optimized formulation, with %EE of ∼ 74 %, demonstrated a particle size and PDI of 107.7 nm and 0.174, respectively. The oral pharmacokinetic profiles of the posaconazole suspension, empty nanoformulation + drug suspension, and drug-loaded nanoformulation were evaluated. The nanoformulation significantly increased maximum plasma concentration and the area under the drug plasma concentration-time curve (∼3.9- and 6.2-fold, respectively) and could be administered without regard to meals. MTT and histopathological examinations were carried out to evaluate the safety of the nanoformulation and results exhibited no significant toxicity. Lymphatic transport was found to be the main mechanism of oral delivery. Caco-2 cell studies demonstrated that the mechanism of delivery was not based on an increase in cellular uptake. Our study represents a promising strategy for the development of phospholipid-based nanoformulations as efficient and safe oral delivery systems.

UV-Vis LED-assisted photo-Fenton process for mineralization of losartan and hydrochlorothiazide: optimization using desirability function

This study presents the results obtained for the optimization of the mineralization of losartan (LOS) and hydrochlorothiazide (HCTZ) using the photo-Fenton process with a UV-Vis LED. Experimental design optimization employing a Doehlert matrix and a global desirability function enabled simultaneous evaluation of multiple responses, with factor fitting providing the best conditions that maximized the mineralization efficiency: Fe²⁺ at 10 mg L^-1 and H₂O₂ at 100 mg L^-1. High rates of mineralization of LOS and HCTZ were obtained, with dissolved organic carbon (DOC); removal of almost 75% after 90 min was observed for both pharmaceuticals. The kinetic model showed that the mineralization followed two regimes in the first minutes, with a fast progression followed by slower activity. The energy consumption calculated for mineralization of LOS and HCTZ at a concentration of 20 mg L^-1 using the UV-Vis LED-assisted photo-Fenton process, at 60 min, was 130 kWh m^-3. The desirability function provides a useful tool for finding optimal experimental conditions for the treatment of effluents with different characteristics. The UV-Vis LED was shown to be a good light source in the photo-Fenton process.