Leveraging Non-Covalent Adaptable Networks to Stabilize Drug-Polymer Systems in Supersaturated Solutions: A Computational and Experimental Approach

This study’s integration of molecular dynamics (MD) simulations with non-covalent adaptable networks (NANs) and corroborative wet lab experiments offers a comprehensive approach to understanding the interactions between ritonavir (RTV) and polymers in supersaturated solutions. This multifaceted study not only explored the stabilization mechanisms facilitated by NANs but also examined the influence of polymer selection on the pharmaceutical properties of RTV, a class III compound known for its slow crystallization rate. This research utilized molecular dynamics simulations to model the intermolecular interactions between RTV and two polymers, Polyvinylpyrrolidone (PVP) K30 and Eudragit L100. These simulations were specifically designed to incorporate the effects of NANs, highlighting their dynamic nature and potential to enhance drug stability and solubility. Simultaneously, wet lab experiments were conducted to measure the nucleation induction times and observe the crystallization behavior of RTV under varying conditions of polymer presence. The experimental data demonstrated a significant extension in nucleation induction time, prolonging the duration from 12 to approximately 64 h when PVP K30 and Eudragit L100 were present. This substantial delay in crystallization was attributed to the strong intermolecular interactions between RTV and the polymers, which were effectively stabilized by the non-covalent bonds within the NANs. These findings were consistently confirmed across both computational and experimental settings, illustrating how NANs can effectively inhibit crystallization and enhance the supersaturation state of RTV. This study successfully demonstrates how the physical and chemical properties of polymers influence the crystallization process of poorly water-soluble drugs such as RTV. Leveraging the synergy between computational simulations and empirical laboratory data, this research provides deep insights into the mechanisms at play, ensuring that drug formulations are optimized for both stability and performance.