Quarterly Journal of Information and Communication Technology ​

The Internet of Bio-Nano Things and the Emergence of Nano-Digital Twins in Telemedicine

Document Type : Original Research Article

Author

Faculty of Nanotechnology Department, School of Advanced Technologies, Iran University of Science and Technology, Tehran, Iran

10.22034/apj.2026.2091021.1068
Abstract
The convergence of emerging technologies, including the Internet of Bio-Nano Things (IoBNT), Artificial Intelligence (AI), Digital Twins, and Nanomedicine, has opened new opportunities for the development of next-generation intelligent systems for cancer diagnosis, monitoring, and treatment. Despite significant advances in each of these fields, a comprehensive framework integrating these technologies into a unified, self-regulating, and closed-loop therapeutic ecosystem has not yet been established. This review proposes a forward-looking conceptual framework in which molecular data acquired by in vivo nanosensors are transmitted through IoBNT to a Nano-Digital Twin, analyzed using artificial intelligence models, and subsequently utilized to guide intelligent nanodrug delivery systems and therapeutic decision-making.
The principal contribution of this study is the integration of four key technologies IoBNT, Artificial Intelligence, Digital Twins, and Nanomedicine within a multilayer closed-loop therapeutic architecture that enables continuous monitoring, real-time analysis, disease progression prediction, and dynamic personalized treatment optimization. From a qualitative perspective, the proposed framework has the potential to improve diagnostic accuracy, enhance the specificity of targeted drug delivery, reduce reactive clinical decision-making, and facilitate the transition toward predictive, adaptive, and personalized medicine. From a functional perspective, the proposed architecture integrates five essential capabilities real-time monitoring, intelligent data analytics, disease progression prediction, adaptive nanodrug delivery, and continuous therapeutic feedback within a unified platform, whereas these capabilities have largely been investigated independently in previous studies.
Finally, this review discusses the major scientific, technical, and translational challenges associated with the clinical implementation of the proposed framework and presents a roadmap for the development of next-generation intelligent nanomedicine and precision medicine. The proposed conceptual framework demonstrates that the convergence of these emerging technologies has the potential to transform conventional healthcare into autonomous, intelligent, and data-driven therapeutic systems for future cancer management.

Keywords


 
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