Optimization of PLGA Nanoparticle Formulation via Microfluidic and Batch Nanoprecipitation Techniques

Area of Science:

• Nanotechnology and Materials Science
• Biomedical Engineering
• Chemical Engineering

Background:

• Poly(lactic-co-glycolic acid) (PLGA) nanoparticles are crucial for drug delivery.
• Scalable and reproducible manufacturing of PLGA nanoparticles presents significant challenges.
• Current production methods often lack precise control over nanoparticle characteristics.

Purpose of the Study:

• To optimize poly(lactic-co-glycolic acid) (PLGA) nanoparticle formulation for drug delivery.
• To compare traditional batch methods with microfluidic approaches for nanoparticle production.
• To investigate the impact of microfluidic geometry and flow parameters on nanoparticle characteristics and stability.

Main Methods:

• Combined experimental nanoprecipitation with computational fluid dynamics (CFD) modeling.
• Utilized Design of Experiments (DoE) for batch process optimization.
• Systematically explored microfluidic mixing by varying flow rate ratio (FRR) and total flow rate (TFR).
• Compared Y-junction and three-inlet microfluidic mixer designs.
• Employed CFD simulations to analyze mixing efficiency and PLGA concentration gradients.
• Used theoretical modeling to predict nanoparticle size based on simulated outlet concentrations.

Main Results:

• The three-inlet microfluidic design produced smaller and more uniform PLGA nanoparticles.
• Nanoparticles fabricated using the three-inlet design exhibited superior post-lyophilization stability.
• CFD simulations confirmed enhanced mixing and interfacial contact in the three-inlet configuration.
• Theoretical predictions of nanoparticle size closely matched experimental observations.
• Microfluidic geometry significantly influences nanoparticle nucleation dynamics.

Conclusions:

• Microfluidic systems, particularly the three-inlet design, offer superior control over PLGA nanoparticle production compared to batch methods.
• The integration of CFD modeling and experimental studies provides a powerful framework for optimizing nanomedicine production.
• This approach enables the rational design of scalable and reproducible manufacturing processes for nanomedicine.
• Understanding microfluidic geometry's role is key to controlling nanoparticle formation for advanced drug delivery applications.