Scholarlink

Purpose <p>This study aimed to enhance Quercetin (QN) efficacy using a nanophytosomal drug delivery system for drug-resistant malaria.</p> Methods <p>Molecular modeling, docking, and DSC studies were performed, followed by optimization using artificial neural network technology.</p> Results <p>The optimization trials identified Drug: PC (Phosphatidylcholine) ratio, DSPE (1,2-Distearoyl-sn-glycero-3-phosphorylethanolamine), and stirring time as critical factors for achieving vesicle size (VS) (11.7&#xa0;nm ± 2.2&#xa0;nm), Poly dispersity index (PDI) (0.211 ± 0.7), and high %Entrapment Efficiency (&gt; 80.46 ± 2.9%). Modeling based on Artificial Neural Networks (ANN) utilizes the Levenberg-Marquardt (LM) algorithm. LM is an optimum algorithm among ANN models which is easy to implement and works fast, exhibited R² = 0.999 and ensured formulation reproducibility. Stability studies confirmed 6 month stability at 4&#xa0;°C. No gross pathological abnormalities were revealed by the necropsy studies at 300&#xa0;mg/kg body weight. Hence from these safety assessment studies, it was concluded that administering oral QN-nanophytosomal formulation up to 300&#xa0;mg/kg did not cause any adverse effects in female rats. The C<sub>max</sub> &amp; AUC<sub>0−∞,</sub> of pure QN was found to be 3.2 ± 8.2&#xa0;µg/mL &amp; 23.58 ± 115.9&#xa0;µg/mL*h respectively and C<sub>max</sub> &amp; AUC<sub>0−∞</sub> of the QN-nanophytosomal formulation was found to be 39.6 ± 4.4&#xa0;µg/mL &amp; 829.8 ± 146.3&#xa0;µg/mL*h respectively. It was observed that C<sub>max</sub> &amp; AUC<sub>0−∞</sub> of QN-nanophytosomal formulation were greatly enhanced when compared to QN suspension. In vitro hemin studies indicated that the QN-nanophytosomal formulation showed greater than 90% inhibition when compared to Quercetin (68.7%) at 70 µM Concentration. The QN-nanophytosomal formulation exhibited sustained drug release (84.6 ± 3.4% at pH 7.4, 95.7 ± 2.7% at pH 5.5 over 72&#xa0;h) and demonstrated 2.3 and 4.5 fold improved antimalarial activity (IC<sub>50</sub>) compared to QN, with no cytotoxicity (CC<sub>50</sub> &gt; 100&#xa0;µg/mL).</p> Conclusion <p>The findings highlight the potential of QN nanophytosomes for improved solubility and targeted malaria treatment.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of Quercetin Nanophytosomes By Artificial Neural Network Modeling

  • 期刊论文

  • 发表日期：

    2026年3月16日

查看全文
  • Bhargav E,
  • Padmanabha Reddy Y,
  • Ramalingam P,
  • Gowthamarajan Kuppusamy

摘要

Purpose

This study aimed to enhance Quercetin (QN) efficacy using a nanophytosomal drug delivery system for drug-resistant malaria.

Methods

Molecular modeling, docking, and DSC studies were performed, followed by optimization using artificial neural network technology.

Results

The optimization trials identified Drug: PC (Phosphatidylcholine) ratio, DSPE (1,2-Distearoyl-sn-glycero-3-phosphorylethanolamine), and stirring time as critical factors for achieving vesicle size (VS) (11.7 nm ± 2.2 nm), Poly dispersity index (PDI) (0.211 ± 0.7), and high %Entrapment Efficiency (> 80.46 ± 2.9%). Modeling based on Artificial Neural Networks (ANN) utilizes the Levenberg-Marquardt (LM) algorithm. LM is an optimum algorithm among ANN models which is easy to implement and works fast, exhibited R² = 0.999 and ensured formulation reproducibility. Stability studies confirmed 6 month stability at 4 °C. No gross pathological abnormalities were revealed by the necropsy studies at 300 mg/kg body weight. Hence from these safety assessment studies, it was concluded that administering oral QN-nanophytosomal formulation up to 300 mg/kg did not cause any adverse effects in female rats. The Cmax & AUC0−∞, of pure QN was found to be 3.2 ± 8.2 µg/mL & 23.58 ± 115.9 µg/mL*h respectively and Cmax & AUC0−∞ of the QN-nanophytosomal formulation was found to be 39.6 ± 4.4 µg/mL & 829.8 ± 146.3 µg/mL*h respectively. It was observed that Cmax & AUC0−∞ of QN-nanophytosomal formulation were greatly enhanced when compared to QN suspension. In vitro hemin studies indicated that the QN-nanophytosomal formulation showed greater than 90% inhibition when compared to Quercetin (68.7%) at 70 µM Concentration. The QN-nanophytosomal formulation exhibited sustained drug release (84.6 ± 3.4% at pH 7.4, 95.7 ± 2.7% at pH 5.5 over 72 h) and demonstrated 2.3 and 4.5 fold improved antimalarial activity (IC50) compared to QN, with no cytotoxicity (CC50 > 100 µg/mL).

Conclusion

The findings highlight the potential of QN nanophytosomes for improved solubility and targeted malaria treatment.