Precision Nanomedicine Converging AI and Multi-Omics: A Comprehensive Review of Cross-disease Applications in Cancer, Diabetes, and Cardiovascular Therapies

Abstract

Aims: Targeting non-specific action, low bioavailability, and systemic toxicity have always been some of the major limitations of medicinal therapies for cancer, diabetes, and CVDs. Here, we provide an overview of a precision nanomaterial integrating AI, multi-omic data, and stimuli-responsive systems for delivery to overcome these limitations. Methods: In cancer, hypoxia-activated nanoparticles, along with enzyme-functionalized carriers, provide excellent penetration in tumours and lessen off-target toxicity. In contrast, the setup of glucose-responsive nanogels and CRISPR-loaded exosomes for diabetes works toward restoration of physiological insulin secretion but confronts problems of metabolic variability. In pathologies affecting the vasculature, peptide-guided nanoparticles and siRNA platforms allow for precise vascular targeting with LDL reduction of 50 per cent. Results: Cross-disease analysis reveals that batch-to-batch variability, immune clearance, and regulatory ambiguities stand convergently as barriers to clinical translation. AI-based design may optimise nanocarrier parameters, while closed-loop theranostic systems make real-time adaptation of the therapy possible. Conclusion: Ethically governing algorithmic bias, CRISPR germline risks, and data privacy issues is of paramount concern here. The way forward is standardised manufacturing, patient-centred trials, and frugal innovations to democratize access to nanotherapies worldwide: targeted, safe, and fair.