Converging Intelligences: Integrating AI-Driven Nanomedicine for Personalized Cancer Theranostics
Year: 2025
Type: article
Abstract: Cancer has also been diverse with its clinical and social burden being overwhelming and the fact that cancer is genetically and pathophysiologically diverse. Single treatment regimens are generally ineffective since each cancer has its biological peculiarity that needs individual intervention. In this regard, nanotechnology-AI integration will introduce a paradigm shift in oncological theranostics.Nanomedical technologies in recent years have yielded diverse products-some products include highly precise diagnostic weapons, a dynamic biosensor probes, and device-controlled drug delivery device systems. Despite these advances, there is little translational efficacy due to interpatient heterogeneity, heterogeneity and complexity of the tumor microenvironment, and tumor progression as a stochastic process. The potential offered by the ability to analyze biomolecular signatures in a highly multifactorial manner through metabolomics and other parallel omics technologies, in connection with AI as the analytical engine of nanotechnology, creates an entirely new dimension in cancer research and treatment. AI gives the power to extract nuances in patient profiles, make treatment prediction and design prescriptive algorithms. Moreover, it enables the development of prospective pharmacokinetic and pharmacodynamic models to optimize the nanocarrier design, individualized therapeutic payloads and minimize off-target toxicity. This review also sketches the emerging landscape of AI enhanced nanotherapeutics in cancer and proposes to investigate clinicians or therapeutic facilities to adhere to unified clinical standards, data standardization, and ethically-sound practice. In our vision of the future of cancer care, traditional paradigms have receded into the past, where modern practice is ever more precision-based, ethically supported, and circumstantially adaptive.
Source: Academic Social Research
Institution: JIS University
Language: English
Subfield: Biomaterials
Field: Materials Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7220503871