A Computational Model for Drug Release from PLGA Implant.

Area of Science:

• Biomaterials Science
• Computational Modeling
• Drug Delivery Systems

Background:

• Emulsion electrospinning is a key technique for creating core-shell nanofibers for controlled drug release.
• Predicting drug release kinetics from poly(lactic-co-glycolic acid) (PLGA) nanofibers is challenging due to system complexity.
• Existing models often simplify the intricate diffusion and degradation processes within nanofibrous matrices.

Purpose of the Study:

• To develop and validate computational models for predicting drug release from PLGA nanofibers produced by emulsion electrospinning.
• To incorporate degradation effects and hydrophobicity into finite element models for enhanced accuracy.
• To present novel 3D modeling approaches for simulating drug diffusion within nanofiber networks.

Main Methods:

• Utilized a finite element methodology to simulate the diffusion mass transport of Rhodamine B, a model drug.
• Developed two distinct 3D computational models: radial 1D finite elements and composite smeared finite elements (CSFEs).
• Included fiber degradation and the partitioning phenomenon (hydrophobicity) at the fiber-surrounding interface in the simulations.

Main Results:

• The computational models, incorporating degradation and hydrophobicity, accurately predicted drug release rates.
• Experimental validation using electrospun PLGA nanofiber mats confirmed the model's predictive capabilities.
• Both the 1D radial and CSFE models demonstrated high accuracy in simulating diffusion processes.

Conclusions:

• The developed finite element models provide efficient and accurate tools for predicting drug transport and release from PLGA nanofiber networks.
• These computational approaches can significantly aid in the design and optimization of nanofibrous drug delivery systems.
• The study highlights the importance of considering degradation and interface phenomena for precise drug release predictions.