The Prediction of the In Vitro Release Curves for PLGA-Based Drug Delivery Systems with Neural Networks DOI Creative Commons
Zheng Zhang,

Bolun Zhang,

Chen Ren

et al.

Pharmaceutics, Journal Year: 2025, Volume and Issue: 17(4), P. 513 - 513

Published: April 14, 2025

Background/Objectives: The accurate prediction of drug release profiles from Poly (lactic-co-glycolic acid) (PLGA)-based delivery systems is a critical challenge in pharmaceutical research. Traditional methods, such as the Korsmeyer-Peppas and Weibull models, have been widely used to describe vitro kinetics. However, these models are limited by their reliance on fixed mathematical forms, which may not capture complex nonlinear nature behavior diverse PLGA-based systems. Method: In response limitations, we propose novel approach—DrugNet, data-driven model based multilayer perceptron (MLP) neural network, aiming predict data at unknown time points fitting curves using key physicochemical characteristics PLGA carriers molecules, well data. We establish dataset through literature review, trained validated determine its effectiveness predicting different curves. Results: Compared traditional Korsmeyer–Peppas semi-empirical MSE DrugNet decreases 20.994 1.561, respectively, (R2) increases 0.036 0.005. Conclusions: These results demonstrate that has stronger ability fit better relationships It can deal with change better, adaptability advantages than overcomes limitations expressions models.

Language: Английский

Nanotechnology-based non-invasive strategies in ocular therapeutics: Approaches, limitations to clinical translation, and safety concerns DOI
Pinal Chaudhari, Shaila A. Lewis, Vivek Ghate

et al.

Contact Lens and Anterior Eye, Journal Year: 2025, Volume and Issue: unknown, P. 102367 - 102367

Published: Jan. 1, 2025

Language: Английский

Citations

2
Insights into ocular therapeutics: A comprehensive review of anatomy, barriers, diseases and nanoscale formulations for targeted drug delivery DOI

Akash Chandel,

Gurpreet Kandav

Journal of Drug Delivery Science and Technology, Journal Year: 2024, Volume and Issue: 97, P. 105785 - 105785

Published: May 15, 2024

Language: Английский

Citations

9
Exploring Non-Cytotoxic, Antioxidant, and Anti-Inflammatory Properties of Selenium Nanoparticles Synthesized from Gymnema sylvestre and Cinnamon cassia Extracts for Herbal Nanomedicine DOI

Sumairan Bi Bi,

Iqra Elahi,

Nimra Sardar

et al.

Microbial Pathogenesis, Journal Year: 2024, Volume and Issue: 192, P. 106670 - 106670

Published: May 9, 2024

Language: Английский

Citations

4
Ophthalmic In Situ Nanocomposite Gel for Delivery of a Hydrophobic Antioxidant DOI Creative Commons
Marta Slavkova, Christina Voycheva, Teodora Popova

et al.

Gels, Journal Year: 2025, Volume and Issue: 11(2), P. 105 - 105

Published: Feb. 2, 2025

The topical administration of in situ hydrogels for ocular pathologies is a promising application strategy providing high effectiveness and patient compliance. Curcumin, natural polyphenol, possesses all the prerequisites successful therapy ophthalmic diseases, but unfortunately its physicochemical properties hurdle practical use. Applying composite thermoresponsive hydrogel formulation embedded with polymer nanoparticles potent to overcome identified drawbacks. In present work we prepared uniform spherical (296.4 ± 3.1 nm) efficiently loaded curcumin (EE% 82.5 2.3%) based on biocompatible biodegradable poly-(lactic-co-glycolic acid). They were thoroughly physicochemically characterized terms FTIR, SEM, TGA, DLS, vitro release following Fickian diffusion (45.62 2.37%), stability over 6 months. Their lack cytotoxicity was demonstrated HaCaT cell lines, potential antioxidant protection also outlined, starting from concentrations as low 0.1 µM reaching 41% at 5 µM. An (17% w/v poloxamer 407 0.1% Carbopol) suitable optimized respect gelation temperature (31.40 0.36 °C), gelling time (8.99 0.28 s) upon tears dilution, gel erosion (90.75 4.06%). Upon curcumin-loaded nanoparticle embedding, appropriate pseudoplastic behavior viscosity 35 °C (2129 24 Pa∙s), 6-fold increase permeation, prolonged h.

Language: Английский

Citations

0
The Prediction of the In Vitro Release Curves for PLGA-Based Drug Delivery Systems with Neural Networks DOI Creative Commons
Zheng Zhang,

Bolun Zhang,

Chen Ren

et al.

Pharmaceutics, Journal Year: 2025, Volume and Issue: 17(4), P. 513 - 513

Published: April 14, 2025

Background/Objectives: The accurate prediction of drug release profiles from Poly (lactic-co-glycolic acid) (PLGA)-based delivery systems is a critical challenge in pharmaceutical research. Traditional methods, such as the Korsmeyer-Peppas and Weibull models, have been widely used to describe vitro kinetics. However, these models are limited by their reliance on fixed mathematical forms, which may not capture complex nonlinear nature behavior diverse PLGA-based systems. Method: In response limitations, we propose novel approach—DrugNet, data-driven model based multilayer perceptron (MLP) neural network, aiming predict data at unknown time points fitting curves using key physicochemical characteristics PLGA carriers molecules, well data. We establish dataset through literature review, trained validated determine its effectiveness predicting different curves. Results: Compared traditional Korsmeyer–Peppas semi-empirical MSE DrugNet decreases 20.994 1.561, respectively, (R2) increases 0.036 0.005. Conclusions: These results demonstrate that has stronger ability fit better relationships It can deal with change better, adaptability advantages than overcomes limitations expressions models.

Language: Английский

Citations

0