Computational perspectives on surfactant-based nanoscale self-assembly and micellar drug delivery: A multiscale review from quantum insights to translational applications

Micellar systems, formed through the self-assembly of amphiphilic molecules, play vital roles in pharmaceuticals, catalysis, nanotechnology and environmental science. Despite extensive experimental research, the molecular mechanisms governing micellization, solubilization and drug encapsulation remain complex and multifactorial. This review consolidates recent advances in computational methodologies that elucidate micellar behavior across multiple scales-from quantum-level interactions to mesoscale dynamics. Density Functional Theory (DFT) provides electronic and energetic insights into surfactant-solute interactions, while Molecular Dynamics (MD) simulations capture the temporal evolution, morphology and thermodynamics of micelle formation. Monte Carlo (MC) methods, COSMO-RS/COSMOmic models and coarse-grained simulations extend these insights to equilibrium structures and solvation energetics. Emerging approaches, including molecular docking, free-energy calculations (MM-PBSA/MM-GBSA) and machine learning (ML), further enhance predictive modeling and formulation design. Case studies highlight the synergistic application of these tools in understanding micellar thermodynamics, solubilization efficiency, shape-size relationships and drug delivery performance. By integrating quantum chemistry, molecular simulation and data-driven modeling, computational micellization has evolved into a predictive, cost-effective and versatile framework. The review highlights how this multiscale approach connects fundamental theoretical understanding with real-world applications, enabling the intelligent design of advanced surfactants, nanoscale delivery systems and sustainable chemical technologies.