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Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.

MiRNA-340 (miR-340) has been found to have tumour-suppressing effects in breast cancer (BC). However, for clinical use, miRNAs need to be delivered safely and effectively to protect them from degradation. In our previous study, we used chitosan complexes as a safe carrier with anti-cancer properties to deliver miR-340 plasmid into 4T1 cells. This study explored further information concerning the anti-cancer impacts of both chitosan and miR-340 plasmid in a murine model of BC. Mice bearing 4T1 cells were intra-tumorally administered miR-340 plasmid-chitosan complexes (miR-340 CC). Afterwards, the potential of miR-340 CC in promoting anti-tumour immune responses was evaluated. MiR-340 CC significantly reduced tumour size, inhibited metastasis, and prolonged the survival of mice. MiR-340 CC up-regulates P-27 gene expression related to cancer cell apoptosis, and down-regulates gene expressions involved in angiogenesis and metastasis (breast regression protein-39 (BRP-39)) and CD163 as an anti-inflammatory macrophages (MQs) marker. Furthermore, CD47 expression as a MQs immune check-point was remarkably decreased after miR-340 CC treatment. The level of IL-12 in splenocytes of miR-340 CC treated mice increased, while the level of IL-10 decreased, indicating anti-cancer immune responses. Our findings display that miR-340 CC can be considered as a promising therapy in BC.