Quantitative multi-agent models for simulating protein release from PLGA bioerodible nano- and microspheres

Area of Science:

• Biomaterials Science
• Computational Modeling
• Drug Delivery Systems

Background:

• Poly(lactide-co-glycolide) (PLGA) is widely used for drug encapsulation and delivery.
• PLGA's tunable dissolution profiles are advantageous but complex to predict.
• Computational models can optimize PLGA particle design and manufacturing.

Purpose of the Study:

• To understand the dissolution phenomena of PLGA micro- and nanospheres.
• To develop and validate agent-based models for predicting PLGA erosion.
• To optimize drug delivery system design and manufacturing parameters.

Main Methods:

• Utilized Cellular Automata (CA) agent-based Monte Carlo (MC) models.
• Simulated PLGA microsphere erosion over large temporal scales.
• Investigated various spatial configurations and dynamic morphologies.

Main Results:

• The multi-agent approach directly observed emergent dissolution profiles during simulated erosion.
• Models demonstrated very good performance when tested against literature experimental data.
• Quantitative discussion provided practical insights into model application.

Conclusions:

• CA-MC models effectively simulate PLGA microsphere erosion and dissolution.
• These models offer a powerful tool for predicting drug release profiles.
• The study validates the use of computational modeling for optimizing PLGA-based drug delivery systems.