Cited by 31Radiopharmaceutical Chemistry and ApplicationsComputational Drug Discovery MethodsArtificial Intelligence in Healthcare and Education

Artificial Intelligence and the Future of Diagnostic and Therapeutic Radiopharmaceutical Development

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Ataeinia, Bahar, Heidari, Pedram·2021·PET Clinics

Abstract

Novel diagnostic and therapeutic radiopharmaceuticals are increasingly becoming a central part of personalized medicine. Continued innovation in the development of new radiopharmaceuticals is key to sustained growth and advancement of precision medicine. Artificial intelligence has been used in multiple fields of medicine to develop and validate better tools for patient diagnosis and therapy, including in radiopharmaceutical design. In this review, we first discuss common in silico approaches and focus on their usefulness and challenges in radiopharmaceutical development. Next, we discuss the practical applications of in silico modeling in design of radiopharmaceuticals in various diseases.

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Crossref · 10.1016/j.cpet.2021.06.008

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  • AI algorithms efficiently navigate vast datasets to reveal subtle patterns and anomalies that might escape human detection in radiopharmaceutical imaging.

    “This partnership boosts the accuracy of radiopharmaceutical imaging, with AI algorithms efficiently navigating through vast datasets to reveal subtle patterns and anomalies that might escape human detection [121].”

    From Radiopharmaceuticals: navigating the frontier of precision medicine and therapeutic innovation (2024) · cites this paper as [121]

    The Introduction discusses AI as a way to speed radiopharmaceutical design, while Applications > CNS discusses computational prediction of tracer binding and accuracy of those predictions. Neither section addresses AI searching imaging datasets for subtle patterns or anomalies that humans might miss; searches for those concepts found no supporting passage in our copy. (LLM, conf=0.74)

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Research works printed but not linked: 5

  1. [30]Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, Brussels, Belgium, 9 4–7, 2006, Proceedings. 2006.
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Authors
Ataeinia, B., & Heidari, P.
Affiliations
  • Massachusetts General Hospital (US)
  • Harvard University (US)
Corresponding author
Heidari, Pedram
Venue
PET Clinics
Publisher
Elsevier BV
Published
2021-10
Volume
16
Issue
4
Pages
513-523
ISSN
1556-8598 (ISSN-L)
OpenAlex
W3189317366
Cited by
31
References
91
Citations by year
2026: 4 · 2025: 12 · 2024: 4 · 2023: 4 · 2022: 5 · 2021: 2
FWCI
0.61
Type
journal article
Language
en
Open access
Locations
  • PET Clinics (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • NCI (K08CA249047)
  • National Institutes of Health
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiopharmaceutical Chemistry and Applications
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
artificial intelligence, radiopharmaceutical development, radiopharmaceutical design, in silico modeling, personalized medicine, precision medicine, diagnostic radiopharmaceuticals, therapeutic radiopharmaceuticals, positron emission tomography
MeSH terms
Artificial Intelligence, Computer Simulation, Forecasting, Humans, Radiopharmaceuticals, Precision Medicine

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