Molecular Simulations of Polymer-based Drug Nanocarriers: From Physical and Structural Properties to Controlled...

Polymer-based drug delivery systems have been extensively studied to overcome the limitations of free drug administration (e.g., poor solubility and stability, rapid degradation and early metabolization, short plasma half-life, low therapeutic efficacy, and occurrence of side effects). Although the vast majority of these drug delivery systems are developed using the traditional time- and resource-intensive trial-and-error method, computational techniques have received considerable attention in order to facilitate and accelerate their understanding and development. In this review, several computational techniques is presented that are commonly used to study polymer-based drug delivery systems. Then, this is discussed several computational investigations of the self-assembly and supramolecular organization of polymer nanocarriers for drug delivery applications, including drug-loaded polymer micelles and polymer prodrug nanoparticles. How modeling approaches can rationalize the drug loading and release from polymer drug delivery systems is further examined, including studies which aim to better understand how physical, chemical, or biological stimuli can trigger the drug release. Machine learning possibilities for extending physics-based molecular simulation efficiency and predictive power have also been briefly discussed.