AI-Based Smart Drug Delivery Systems: Integrating Artificial Intelligence and Nanotechnology

The coming of convergences between artificial intelligence (AI) and nanotechnology marks an innovative age in the delivery system of pharmaceutical drugs. In this paper, the author introduces a full-fledged framework, which is called the AI-Nano Integrated Delivery System (ANIDS), that uses deep learning, reinforcement learning, and generative adversarial networks (GANs) to design, optimise, and monitor smart nanocarrier platforms to deliver therapeutic entities. We propose a multi-omics patient measurement system combined with physicochemical nanoparticle descriptors so as to achieve personalised, stimulusreactive drug delivery with minimal off-target toxicity. Experiment simulation on confirmed public datasets (NanoMine, eNanoMapper, and Nano-Tumor Database) show that ANIDS is able to operate with a targeting accuracy of 96.2% and drug encapsulation efficiency of 93.8% and area under ROC curve (AUC) of 0.97 which is above 5-14 percentages in relation to the state of art baselines. A simulation of cytotoxicity on the cancer cell lines of MCF-7 breast cancer reveal that the rate at which cancer cells were killed increased 78 percent at an IC 50 of 0.6 uM compared to conventional doxorubicin which was 2.8 uM. The fact that the proposed approach is the best solution, and that it is generalisable is proven by comparison with ten other studies conducted before.

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