مقالات پذیرفته شده در نهمین کنگره بین المللی زیست پزشکی
Artificial Intelligence-Driven Smart Nanosystems: A Revolution in Personalized Medicine with Gene Delivery and Drug Delivery.
Artificial Intelligence-Driven Smart Nanosystems: A Revolution in Personalized Medicine with Gene Delivery and Drug Delivery.
mahdieh kamali,1,*
1. Department of Biotechnology, Faculty of Basic Sciences, University of Maragheh, Maragheh, Iran
Introduction: Personalized medicine has revolutionized biomedical sciences by tailoring treatments to patients genetic, physiological, and environmental profiles. The convergence of artificial intelligence (AI) and nanotechnology offers unprecedented opportunities to enhance diagnostic precision, therapeutic efficacy, and safety in targeted drug and gene delivery. Smart nano systems, including lipid nanoparticles, polymeric nanoparticles, DNA/peptide nanostructures, exosomes, and inorganic nanoparticles, guided by AI, effectively overcome biological barriers such as the blood-brain barrier and disease microenvironment heterogeneity. This systematic review explores the role of this synergy in the design, optimization, and clinical translation of nanocarriers while addressing key challenges.
Methods: The inclusion criteria covered studies exploring the use of artificial intelligence in the design, optimization, or clinical application of nanosystems for drug and gene delivery, with a particular emphasis on cancer, neurological disorders, and CRISPR/Cas9-based gene therapy. Studies were excluded if they were non-biomedical in scope, published in languages other than English, or lacked experimental or simulation data. Both qualitative synthesis and quantitative evaluation were applied to the selected literature to highlight current research trends and to identify existing knowledge gaps.
Results: The analysis revealed that machine learning approaches, such as support vector machines, random forest models, and advanced deep neural networks, have substantially contributed to refining the physicochemical profiles of nanoparticles, particularly with respect to their size, surface charge, and chemical composition. In parallel, molecular dynamics simulations enhanced by artificial intelligence have provided accurate predictions regarding the stability and self-assembly behavior of DNA- and peptide-based nanostructures, offering valuable guidance for the rational development of targeted delivery platforms. Predictive modeling strategies further enabled the simulation of nanoparticle–cell interactions, protein corona dynamics, and biodistribution patterns, ultimately supporting improved blood–brain barrier penetration and more precise tumor localization. In addition, stimuli-responsive nanosystems—sensitive to environmental or external triggers such as pH, temperature, light, or ultrasound—have demonstrated real-time monitoring and controlled release capacities that markedly improved the delivery efficiency of mRNA molecules and CRISPR elements. Exosomes optimized through AI-based design also showed enhanced drug loading and tissue-specific targeting, translating into higher therapeutic effectiveness in both oncology and neurodegenerative disease contexts.
Conclusion: The integration of AI and smart nanosystems has transformed personalized medicine by accelerating design, modeling complex biological interactions, and enhancing targeted delivery, thereby improving treatment precision and safety. Nanocarriers show immense potential in gene therapy, cancer, and neurological disorders. Future research should focus on robust regulatory frameworks, scalable clinical trials, integration with omics data, and transparent AI algorithms to ensure sustainable and inclusive therapeutic advancements.