Innovative strategies to overcome cancer drug resistance: from nanodelivery systems to targeted therapeutics

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Cancer drug resistance, driven by complex genetic mutations, epigenetic plasticity, and tumor microenvironment interactions, remains the primary cause of therapeutic failure and poor patient survival. This review critically synthesizes current resistance mechanisms to propose a unified framework that maps specific molecular drivers to corresponding therapeutic interventions, ranging from conventional chemosensitizers to emerging AI-guided strategies. We demonstrate that while chemosensitizers effectively reverse efflux-mediated resistance and that targeted therapies address specific oncogenic drivers, their efficacy is often limited by biological barriers; conversely, nanoparticle delivery systems significantly increase bioavailability, and CRISPR/Cas9 offers precise correction of intrinsic genetic defects. Crucially, we identify that no single modality is universally sufficient; instead, maximal therapeutic impact arises from the strategic cross-talk between technologies, such as the use of AI to predict resistance evolution and optimize the timing of combination therapies or nanocarrier-delivered gene editing. Future clinical success depends on shifting from isolated treatment protocols to interdisciplinary, data-driven personalized medicine that dynamically adapts to the evolving landscape of tumor resistance, ultimately transforming fatal malignancies into manageable chronic conditions. • Drug resistance remains a major barrier in cancer therapy, as cancer cells adapt and tolerate treatments, resulting in poorer patient outcomes. • Cancer cells employ complex genetic, epigenetic, and microenvironmental mechanisms to evade drug effects and promote survival. • Multidrug resistance often involves ABC transporters such as P-glycoprotein, which actively expel anticancer drugs from cells. • Advances such as targeted therapies, nanotechnology-based delivery, and adaptive dosing have improved outcomes, but resistance persists. • Comprehensive strategies integrating genomics, proteomics, and machine learning are also vital for overcoming cancer drug resistance.