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用于个性化纳米医学的人工智能:从材料选择到患者预后

Artificial intelligence for personalized nanomedicine; from material selection to patient outcomes.

作者信息

Mazumdar Hirak, Khondakar Kamil Reza, Das Suparna, Halder Animesh, Kaushik Ajeet

机构信息

Department of Computer Science and Engineering, Adamas University, Kolkata, India.

School of Sciences, Woxsen University, Hyderabad, India.

出版信息

Expert Opin Drug Deliv. 2025 Jan;22(1):85-108. doi: 10.1080/17425247.2024.2440618. Epub 2024 Dec 15.

Abstract

INTRODUCTION

Artificial intelligence (AI) is changing the field of nanomedicine by exploring novel nanomaterials for developing therapies of high efficacy. AI works on larger datasets, finding sought-after nano-properties for different therapeutic aims and eventually enhancing nanomaterials' safety and effectiveness. AI leverages patient clinical and genetic data to predict outcomes, guide treatments, and optimize drug dosages and forms, enhancing benefits while minimizing side effects. AI-supported nanomedicine faces challenges like data fusion, ethics, and regulation, requiring better tools and interdisciplinary collaboration. This review highlights the importance of AI regarding patient care and urges scientists, medical professionals, and regulators to adopt AI for better outcomes.

AREAS COVERED

Personalized Nanomedicine, Material Discovery, AI-Driven Therapeutics, Data Integration, Drug Delivery, Patient Centric Care.

EXPERT OPINION

Today, AI can improve personalized health wellness through the discovery of new types of drug nanocarriers, nanomedicine of specific properties to tackle targeted medical needs, and an increment in efficacy along with safety. Nevertheless, problems such as ethical issues, data security, or unbalanced data sets need to be addressed. Potential future developments involve using AI and quantum computing together and exploring telemedicine i.e. the Internet-of-Medical-Things (IoMT) approach can enhance the quality of patient care in a personalized manner by timely decision-making.

摘要

引言

人工智能(AI)正在通过探索新型纳米材料以开发高效疗法来改变纳米医学领域。人工智能处理更大的数据集,为不同治疗目标寻找所需的纳米特性,最终提高纳米材料的安全性和有效性。人工智能利用患者的临床和基因数据来预测结果、指导治疗以及优化药物剂量和剂型,在将副作用降至最低的同时提高疗效。人工智能支持的纳米医学面临数据融合、伦理和监管等挑战,需要更好的工具和跨学科合作。本综述强调了人工智能在患者护理方面的重要性,并敦促科学家、医学专业人员和监管机构采用人工智能以取得更好的成果。

涵盖领域

个性化纳米医学、材料发现、人工智能驱动的治疗、数据整合、药物递送、以患者为中心的护理。

专家观点

如今,人工智能可以通过发现新型药物纳米载体、针对特定医疗需求的具有特定性质的纳米医学以及提高疗效和安全性来改善个性化健康状况。然而,伦理问题、数据安全或数据集不平衡等问题需要得到解决。未来潜在的发展包括将人工智能与量子计算结合使用,以及探索远程医疗,即医疗物联网(IoMT)方法可以通过及时决策以个性化方式提高患者护理质量。

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