Integrating AI Models and Nanotechnology for Precision and Personalized Medicine: Current Achievements and Prospects

The synergistic combination of artificial intelligence (AI) and nanotechnology is reshaping the landscape of personalized medicine by enabling predictive, data-driven, and patient-specific therapeutic strategies. Nanotechnology offers unique opportunities to design nanoscale systems for sensitive diagnostics, targeted drug delivery, and controlled therapeutic release, while AI provides advanced computational tools capable of analyzing complex and heterogeneous biomedical datasets. Together, these technologies address the limitations of conventional treatment approaches by accounting for individual variability in genetics, disease biology, and therapeutic response. This chapter explores the role of AI-enabled nanotechnology in precision healthcare, with emphasis on disease detection, treatment planning, and personalized drug delivery. The use of machine learning and deep learning techniques in molecular imaging, biosensing, and digital pathology is discussed, highlighting their contribution to early diagnosis, accurate disease characterization, and real-time monitoring. The chapter further examines the use of AI-driven models to support pharmacogenomics and personalized drug development by integrating multi-omics data, clinical records, and real-world evidence to predict patient-specific drug responses and optimize drug strategies. In addition, AI-assisted modeling aids in the rational design of nanoparticles with tailored physicochemical properties to improve therapeutic efficiency and minimize adverse effects. Emerging concepts such as intelligent nanodevices, adaptive delivery platforms, and AI-guided nanomedicine optimization are also addressed. The integration of AI with advanced therapeutic modalities, including gene therapy and precision oncology, is presented as a promising direction for future research.