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纳米技术中的人工智能在疾病治疗中的应用。

Artificial intelligence in nanotechnology for treatment of diseases.

机构信息

Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Department of Pharmaceutics and Pharmaceutical Nanotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

J Drug Target. 2024 Dec;32(10):1247-1266. doi: 10.1080/1061186X.2024.2393417. Epub 2024 Aug 27.

Abstract

Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.

摘要

基于纳米的药物传递系统 (DDS) 已证明有能力解决治疗剂带来的挑战,提高药物效率并减少副作用。各种具有独特特性的纳米颗粒 (NPs) 被用作 DDS,从而在不同疾病中得到了广泛的应用。然而,实验室流程的复杂性、成本和耗时性质、大量的数据以及数据分析的挑战,促使人们整合了人工智能 (AI) 工具。AI 已被用于设计、表征和制造药物传递纳米系统,以及预测治疗效率。AI 具有根据个体患者因素个性化药物传递、优化配方设计和预测药物特性的潜力。通过利用 AI 和大型数据集,可以加速开发安全有效的 DDS,最终改善患者的结果并推动药物科学的发展。本文综述了 AI 在纳米 DDS 开发中的作用,重点介绍了其治疗应用。AI 在 DDS 中的应用有可能彻底改变治疗优化并改善患者护理。

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