Development of nanoparticles for precision medicine and spatio-temporal computational modeling of their release and distribution in a pathophysiological environment

Visual impairment caused by retinal pathologies remains a major global health challenge, with current therapeutic strategies limited by poor drug penetration to the posterior segment and low patient adherence. This thesis presents the development and integration of a polymeric nanoparticle (PNP) platform and a computational fluid dynamics (CFD) framework for controlled ocular drug delivery. The dual in vitro–in silico approach aimed to rationalize the design of biodegradable, mucoadhesive, and light-responsive carriers while building a predictive model of their transport within ocular microvasculature. Poly(lactic-co-glycolic acid) (PLGA) nanoparticles were produced through both oil-in-water (O/W) emulsion and acetonitrile-based nanoprecipitation routes. The formulation strategy systematically explored solvent composition, surfactant type, polymer ratio, and chitosan-coating conditions. The optimized O/W route yielded spherical nanoparticles with Z-averages of 330–380 nm (PDI ≈ 0.15) and DEX loading of 6.4–6.7 wt%, while chitosan coating increased size to ~800 nm and reversed ζ-potential to +40–70 mV. Nanoprecipitation produced smaller and more uniform cores (~90–100 nm, PDI ≈ 0.15) with higher encapsulation (≈8.9 wt% drug, ≈55 % efficiency) and robust stability after coating. IR820 was successfully co-loaded as a near-infrared (NIR)-responsive dye, maintaining colloidal integrity. Release assays revealed biphasic kinetics governed by diffusion in the early phase (Higuchi R2 ≈ 0.99) and slower matrix relaxation at longer times, with on-demand enhancement under NIR irradiation (2–5× increase in early release rate). Empirical release coefficients were embedded into ANSYS Fluent through a custom User-Defined Function implementing Higuchi-type kinetics within a Eulerian–Lagrangian framework. Simulations reproduced drug dispersion in both scaled and physiological microvascular geometries, capturing convection-driven spreading in large networks and diffusion-dominated retention at capillary scales. Quantitative agreement with literature data suggested the model’s mechanistic validity and established a foundation for quantitative predictive simulations. Overall, this work consolidates formulation science and computational modeling into a unified design platform. It delivers two validated PLGA-based nanoparticle families and a CFD tool that collectively enable rational optimization of ocular nanomedicines. The resulting in vitro–in silico pipeline offers a reproducible, extensible framework for light-tunable drug delivery to the posterior eye, supporting future translational studies and the progressive replacement of animal experimentation through simulation-guided formulation design.