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纳米放射性药物:设计原理、放射性标记策略及生物医学应用。

Nanoradiopharmaceuticals: Design Principles, Radiolabeling Strategies, and Biomedicine Applications.

作者信息

Núñez-Salinas Andrés, Parra-Garretón Cristian, Acuña Daniel, Peñaloza Sofía, Günther Germán, Bollo Soledad, Arriagada Francisco, Morales Javier

机构信息

Universidad Andres Bello, Escuela de Química y Farmacia, Facultad de Medicina. 8370016. Santiago. Chile.

Departamento de Ciencias y Tecnología Farmacéutica, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago 8380492, Chile.

出版信息

Pharmaceutics. 2025 Jul 14;17(7):912. doi: 10.3390/pharmaceutics17070912.


DOI:10.3390/pharmaceutics17070912
PMID:40733120
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12300555/
Abstract

Nanoradiopharmaceuticals integrate nanotechnology with nuclear medicine to enhance the precision and effectiveness of radiopharmaceuticals used in diagnostic imaging and targeted therapies. Nanomaterials offer improved targeting capabilities and greater stability, helping to overcome several limitations. This review presents a comprehensive overview of the fundamental design principles, radiolabeling techniques, and biomedical applications of nanoradiopharmaceuticals, with a particular focus on their expanding role in precision oncology. It explores key areas, including single- and multi-modal imaging modalities (SPECT, PET), radionuclide therapies involving beta, alpha, and Auger emitters, and integrated theranostic systems. A diverse array of nanocarriers is examined, including liposomes, micelles, albumin nanoparticles, PLGA, dendrimers, and gold, iron oxide, and silica-based platforms, with an assessment of both preclinical and clinical research outcomes. Theranostic nanoplatforms, which integrate diagnostic and therapeutic functions within a single system, enable real-time monitoring and personalized dose optimization. Although some of these systems have progressed to clinical trials, several obstacles remain, including formulation stability, scalable manufacturing, regulatory compliance, and long-term safety considerations. In summary, nanoradiopharmaceuticals represent a promising frontier in personalized medicine, particularly in oncology. By combining diagnostic and therapeutic capabilities within a single nanosystem, they facilitate more individualized and adaptive treatment approaches. Continued innovation in formulation, radiochemistry, and regulatory harmonization will be crucial to their successful routine clinical use.

摘要

纳米放射性药物将纳米技术与核医学相结合,以提高用于诊断成像和靶向治疗的放射性药物的精度和有效性。纳米材料具有更好的靶向能力和更高的稳定性,有助于克服多种局限性。本综述全面概述了纳米放射性药物的基本设计原则、放射性标记技术和生物医学应用,特别关注它们在精准肿瘤学中不断扩大的作用。它探讨了关键领域,包括单模态和多模态成像方式(单光子发射计算机断层扫描、正电子发射断层扫描)、涉及β、α和俄歇发射体的放射性核素治疗以及集成的诊疗系统。研究了各种各样的纳米载体,包括脂质体、胶束、白蛋白纳米颗粒、聚乳酸-羟基乙酸共聚物、树枝状大分子以及基于金、氧化铁和二氧化硅的平台,并评估了临床前和临床研究结果。诊疗纳米平台在单个系统中整合了诊断和治疗功能,能够进行实时监测和个性化剂量优化。尽管其中一些系统已进入临床试验阶段,但仍存在一些障碍,包括制剂稳定性、可扩展制造、法规合规性以及长期安全性考虑。总之,纳米放射性药物在个性化医疗领域,尤其是肿瘤学领域,是一个充满前景的前沿领域。通过在单个纳米系统中结合诊断和治疗能力,它们促进了更个性化和适应性更强的治疗方法。在制剂、放射化学和法规协调方面持续创新对于它们成功常规临床应用至关重要。

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本文引用的文献

[1]
Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.

Biomolecules. 2025-3-20

[2]
Highlight selection of radiochemistry and radiopharmacy developments by editorial board.

EJNMMI Radiopharm Chem. 2025-3-25

[3]
Deep learning in nuclear medicine: from imaging to therapy.

Ann Nucl Med. 2025-5

[4]
Deep learning models in classifying primary bone tumors and bone infections based on radiographs.

NPJ Precis Oncol. 2025-3-13

[5]
Nano-Radiopharmaceuticals in Colon Cancer: Current Applications, Challenges, and Future Directions.

Pharmaceuticals (Basel). 2025-2-14

[6]
Green Nuclear Medicine and Radiotheranostics.

J Nucl Med. 2025-3-3

[7]
Image Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review.

Sensors (Basel). 2024-12-18

[8]
Design and development of nanoprobes radiolabelled with Tc for the diagnosis and monitoring of therapeutic interventions in oncology preclinical research.

EJNMMI Radiopharm Chem. 2024-10-29

[9]
Nanoscale Radiotheranostics for Cancer Treatment: From Bench to Bedside.

Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2024

[10]
Designing nanotheranostics with machine learning.

Nat Nanotechnol. 2024-12

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