Nanomedicines Targeting Metabolic Pathways in the Tumor Microenvironment: Future Perspectives and the Role of AI
Abstract
Background: Tumor cells engage in continuous self-replication by utilizing a large number of resources and capabilities, typically within an aberrant metabolic regulatory network to meet their own demands. This metabolic dysregulation leads to the formation of the tumor microenvironment (TME) in most solid tumors. Nanomedicines, due to their unique physicochemical properties, can achieve passive targeting in certain solid tumors through the enhanced permeability and retention (EPR) effect, or active targeting through deliberate design optimization, resulting in accumulation within the TME. The use of nanomedicines to target critical metabolic pathways in tumors holds significant promise. However, the design of nanomedicines requires the careful selection of relevant drugs and materials, taking into account multiple factors. The traditional trial-and-error process is relatively inefficient. Artificial intelligence (AI) can integrate big data to evaluate the accumulation and delivery efficiency of nanomedicines, thereby assisting in the design of nanodrugs. Methods: We have conducted a detailed review of key papers from databases, such as ScienceDirect, Scopus, Wiley, Web of Science, and PubMed, focusing on tumor metabolic reprogramming, the mechanisms of action of nanomedicines, the development of nanomedicines targeting tumor metabolism, and the application of AI in empowering nanomedicines. We have integrated the relevant content to present the current status of research on…
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