Smart Nanomedicines for Cancer Therapy

The junction of Artificial Intelligence (AI) with nanotechnology has transformed cancer research by enabling the design of intelligent, personalized drug delivery systems. AI-driven models can process complex biological and chemical datasets to predict Nanoparticle (NP) behavior, optimize formulation parameters, and simulate interactions within the Tumor Microenvironment (TME). This data-driven approach allows for the rational design of smart nanomedicines capable of targeted, stimuli-responsive, and controlled drug release. The chapter outlines the fundamental principles of smart nanomedicine design, emphasizing the roles of materials such as polymeric NPs, liposomes, dendrimers, inorganic nanostructures, and hybrid or biomimetic carriers. It further explores how AI can enhance every stage of development, from NPs synthesis and toxicity prediction to molecular docking and therapeutic optimization. Special attention is given to AI-assisted modeling of the TME to create adaptive, patient-specific nanocarriers. Despite these advances, challenges persist in data standardization, model interpretability, large-scale production, and regulatory acceptance. By integrating nanoinformatics, digital twin simulations, and multiomics analytics, AI-driven smart nanomedicine offers a promising pathway toward safer, more efficient, and truly personalized cancer therapies.