Artificial intelligence assisted design of nanomedicines for colorectal cancer diagnosis and therapy: Advances, challenges, and future directions

Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide, with an increasing incidence in both high- and low-income countries. Despite advances in colonoscopy, imaging, molecular biomarker testing, and multimodal therapeutic regimens, limitations in early detection, tumor heterogeneity, and resistance to conventional therapy continue to hinder effective management of CRC. Nanomedicine offers transformative opportunities for precision diagnosis and therapy by enabling targeted delivery, controlled drug release, and multimodal imaging. Concurrently, artificial intelligence (AI), including machine learning (ML), deep learning (DL), and emerging transformer-based architectures, has revolutionized the interpretation of biomedical data and guided the rational design of nanocarriers for drug delivery applications. The synergistic integration of artificial intelligence and nanotechnology has accelerated the discovery of CRC-specific biomarkers, improved formulation optimization, enabled predictive pharmacokinetic/pharmacodynamic modeling, and facilitated the design of adaptive clinical trials. Recent breakthroughs include AI-driven histopathology and imaging analysis for early CRC detection, with AI-assisted colonoscopy demonstrating sensitivity improvements of up to 94 to 97% and accuracy gains of 10 to 20% compared to standard methods. However, major challenges remain, including limited access to large, annotated CRC datasets, the interpretability of AI models in clinical decision-making, the reproducibility of complex nanoparticle synthesis, and regulatory gaps in nanomedicine. This review synthesizes the current advances in AI-assisted nanomedicine for CRC diagnosis and therapy, critically evaluates the translational barriers, and outlines future research trajectories. Ultimately, multidisciplinary collaboration across oncology, nanotechnology, the design of adaptive clinical trials, science, and regulatory science is essential to realize the full potential of AI-powered nanomedicine in CRC management