Uso della Dissipative Particle Dynamics per simulare l’incapsulamento di farmaci all’interno di micelle di Pluronico F68 = On the use of Dissipative Particle Dynamics to simulate drugs encapsulation whithin Pluronic F68

Drug encapsulation represents one of the most relevant topics in pharmaceutical sciences, particularly through the use of block copolymer materials in the form of spherical micelles. In this context, Pluronics are widely studied thanks to their biocompatibility and thermosensitivity. They are non-ionic amphiphilic copolymers consisting of a hydrophobic central chain of polypropylene oxide (PPO) and two hydrophilic lateral chains of polyethylene oxide (PEO). Due to their amphiphilic nature, Pluronics self-assemble into micellar structures in aqueous solutions above a critical concentration and temperature, known respectively as CMC and CMT. Among these, a particularly interesting system is represented by Pluronic F68 which, in aqueous solution at 45% by weight, exhibits a peculiar thermosensitive transition. At high temperatures, it organizes into an ordered supramolecular structure, specifically a body-centered cubic (BCC) phase, characterized by solid-like rheological behavior. This transition is of particular interest for drug delivery applications. This thesis aims to explore the use of Dissipative Particle Dynamics to simulate two drug/polymer encapsulation systems, consisting respectively of Pluronic F68 with Diclofenac, and Pluronic F68 with Diclofenac sodium, a widely used non-steroidal anti-inflammatory drug. The goal is to support experiments by analyzing the structural behavior and encapsulation capacity. For each system, four different drug concentrations are considered, namely 0.015 mol/L, 0.020 mol/L, 0.075 mol/L, and 0.100 mol/L. Dissipative Particle Dynamics (DPD) is a mesoscale simulation technique capable of exploring the mesoscale, a region not accessible to fully atomistic simulations but essential for describing microstructure formation and its impact on rheological properties. The computational advantage of DPD stems from its coarse-grained approach, in which groups of atoms are represented as larger units, called beads, thus simplifying the description compared to atomistic simulations. All simulations were carried out using LAMMPS.