The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Potent candidates for Targeted Auger Therapy: Production and radiochemical considerations
Abstract
Targeted Auger Therapy represents great potential for the therapy of diseases which require a high degree of selectivity on the cellular level (e.g. for therapy of metastatic cancers). Due to their high Linear Energy Transfer (LET), Auger emitters, combined with selective biological systems which enable delivery of radionuclides close to the DNA of the targeting cell, can be extremely selective and powerful treatment tools. There are two main aspects associated with the development of efficient radiopharmaceuticals based on Auger Emitters: a) the availability of suitable Auger-emitting radionuclides for therapy and b) the design of targeting vectors which can deliver Auger emitters into/close to the nucleus. In the present review, we address the first aspect by defining important parameters for the selection of radionuclides for application to Targeted Auger Therapy and form a categorized list of the most promising radionuclides, their possible production routes, and their use in the synthesis of radiopharmaceuticals.
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Cites
Controlled drug delivery vehicles for cancer treatment and their performance
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Radioactive Main Group and Rare Earth Metals for Imaging and Therapy
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THE RELATIVE IMPACT AND FUTURE BURDEN OF PROSTATE CANCER IN THE UNITED STATES
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Metadata
- Authors
- Filosofov, D., Kurakina, E., & Radchenko, V.
- Venue
- Nuclear Medicine and Biology
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 94-95
- Pages
- 1-19
- ISSN
- 0969-8051 (ISSN-L)
- OpenAlex
- W3111132909
- Cited by
- 341
- References
- 52
- FWCI
- 32.61
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.