Bahrami Yadollah, Bolideei Mansoor, Mohammadzadeh Sara, Gahrouei Razieh Bahrami, Mohebbi Elham, Haider Khawaja Husnain, Barzigar Rambod, Mehran Mohammad Javad
Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran; Department of Medical Biotechnology, Faculty of Medicine, Kermanshah University of Medical Sciences, Kermanshah 6714415185, Iran; Department of Medical Biotechnology, School of Medicine, College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia; Advanced Marine Biomanufacturing Laboratory, Centre for Marine Bioproducts Development, College of Medicine and Public Health, Flinders University, Adelaide, SA 5042, Australia.
Department of Respiratory and Critical Care Medicine, the Center for Biomedical Research, NHC Key Laboratory of Respiratory Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Immunology, Chabahar Faculty of Medical Sciences, Chabahar, Iran.
Int J Pharm. 2025 Aug 29;684:126096. doi: 10.1016/j.ijpharm.2025.126096.
Vaccines have long been crucial in safeguarding public health by preventing and controlling infectious diseases. However, traditional vaccine development methods face challenges in efficiency, cost, and response time to emerging pathogens. Recent progress in art AI and nanotechnology is revolutionizing this landscape, offering innovative solutions for vaccine design, delivery, and optimization. This manuscript examines the transformative impact of AI and nanotechnology on advancing vaccine development, highlighting their synergistic effect in overcoming traditional limitations. AI, particularly machine learning (ML) and deep learning (DL) algorithms, facilitates rapid identification of immunogenic antigens and epitopes by analyzing vast genomic, proteomic, and immunological datasets. These computational tools optimize vaccine design by predicting antigen stability, immunogenicity, and efficacy, as exemplified by the expedited development of COVID-19 vaccines. Nanotechnology complements these advancements by providing engineered nanoparticles (NPs), including liposomes, polymeric NPs, and biomimetic systems, that enhance antigen delivery, stability, and immune activation. Innovations such as virus-like particles (VLPs) and immune-stimulating complexes (ISCOMs) further enhance vaccine safety and efficacy by mimicking natural infection processes to trigger robust, targeted immune responses. Integrating AI and nanotechnology presents remarkable opportunities for developing personalized immunization strategies. AI algorithms can assess individual immune profiles to design customized vaccines, while nanotechnology enables precise delivery and controlled release of antigens. This interdisciplinary approach accelerates vaccine development, ensuring both safety and efficacy, and lays the foundation for universal vaccines and cancer vaccines that target complex pathogens and non-infectious diseases. Together, AI and nanotechnology herald a new era in vaccinology, enabling the development of vaccines that are faster, more precise, and highly adaptable to emerging and complex health challenges.
长期以来,疫苗在预防和控制传染病以保障公众健康方面一直至关重要。然而,传统的疫苗开发方法在效率、成本以及对新出现病原体的响应时间方面面临挑战。人工智能(AI)和纳米技术的最新进展正在彻底改变这一局面,为疫苗设计、递送和优化提供创新解决方案。本文探讨了AI和纳米技术对推进疫苗开发的变革性影响,强调了它们在克服传统局限性方面的协同作用。AI,特别是机器学习(ML)和深度学习(DL)算法,通过分析大量的基因组、蛋白质组和免疫学数据集,有助于快速识别免疫原性抗原和表位。这些计算工具通过预测抗原稳定性、免疫原性和功效来优化疫苗设计,新冠疫苗的加速开发就是例证。纳米技术通过提供工程化纳米颗粒(NP)来补充这些进展,这些纳米颗粒包括脂质体、聚合物纳米颗粒和仿生系统,可增强抗原递送、稳定性和免疫激活。诸如病毒样颗粒(VLP)和免疫刺激复合物(ISCOM)等创新进一步提高了疫苗的安全性和功效,通过模拟自然感染过程来触发强大的、有针对性的免疫反应。整合AI和纳米技术为开发个性化免疫策略带来了显著机遇。AI算法可以评估个体免疫概况以设计定制疫苗,而纳米技术能够实现抗原的精确递送和控释。这种跨学科方法加速了疫苗开发,确保了安全性和有效性,并为针对复杂病原体和非传染性疾病的通用疫苗和癌症疫苗奠定了基础。AI和纳米技术共同开创了疫苗学的新纪元,使疫苗的开发更快、更精确,并且能够高度适应新出现的和复杂的健康挑战。