## 2 Materials and Methods
### Production Runs and Data Collection Using Molecular Dynamics Simulations  
We conducted molecular dynamics simulations on four distinct complexes: RTV with Eudragit L100 at 500 ppm (E1), RTV with Eudragit L100 at 2000 ppm (E2), RTV with PVP K30 at 500 ppm (P1), and RTV with PVP K30 at 2000 ppm (P2). These simulations were carried out using GROMACS 2016.3 software [33; 34; 35], employing the AMBER99 SB-ILDN and AMBER General Force Fields (GAFF) to model the systems [36; 37]. The topology and parameterization of RTV, Eudragit L100, and PVP K30 were managed through the AnteChamber Python Parser interface (ACPYPE) [38], and long-range electrostatic interactions were calculated using the Ewald Particle Mesh method [39]. Sodium (Na+) and chloride (Cl\(-\)) ions were added to ensure the systems were neutral. The molecular weights of PVP K30 and Eudragit L100 were explicitly calculated to accurately model polymer chains in the simulations. For PVP K30, the average molecular weight (Mw) is 50,000 g/mol, and the molecular weight of its monomer, vinylpyrrolidone, is 111.14 g/mol. The degree of polymerization (DP) was determined using the formula:  
\[DP=\frac{\text{Mw}(\text{polymer})}{\text{Mw}(\text{monomer})}=\frac{50,00}{114.14}\approx 450\]  
Figure 2: Two-dimensional visualization of RTV, PVP K30, and Eudragit L100 for the creation of drug–polymer systems.  
Hence, the polymer chain was constructed with 450 monomer units. For Eudraggit L100, a random copolymer of methacrylic acid (86.09 g/mol) and methyl methacrylate (100.12 g/mol) in a 1:1 ratio, the molecular weight of the repeating unit was calculated as:  
\[\text{Mw}(\text{repeat unit})=\frac{86.09+100.12}{2}=93.11\,\text{g/mol}\]  
Using the polymer's average molecular weight of 130,000 g/mol, the degree of polymerization was determined as:  
\[DP=\frac{\text{Mw}(\text{polymer})}{\text{Mw}(\text{monomer})}=\frac{130,000}{9 3.11}\approx 1396\]  
Thus, the polymer chain for Eudragit L100 was modeled with 1396 monomer units, distributed randomly between methacrylic acid and methyl methacrylate. These polymer chains were parameterized using force fields compatible with their chemical properties and integrated into the simulation. The preparation for these simulations involved several key steps. We first performed minimization to resolve any steric clashes and then heated the systems to 25 \({}^{\circ}\)C (298 K) to ensure thermal stability. This was followed by the equilibration of both temperature and pressure to create a stable simulation environment. During the production run, a timestep of 2 femtoseconds was used to capture detailed dynamic behavior. Each system was simulated for 100 nanoseconds, and we carefully analyzed energy, pressure, temperature, and Root Mean Square Deviation (RMSD) to assess stability. This thorough approach ensured that the simulations were reliable and provided a solid basis for understanding the interactions within each complex. Additionally, we conducted analyses of RDF, radius of gyration (Rg), Solvent-Accessible Surface Area (SASA), and hydrogen bonding (Hbond) to obtain a deeper understanding of the structural and dynamic properties of the systems, using Grace-5.1.22 and Microsoft Excel 365 for data visualization and analysis.