Authors
Lansaol Yang, Michael E Bryan, Eduardo Veiga, Ian Lowenhoff, Alex Wan, Isam Mina, Tracey Allen, Javier Antonio Alfaro, Gareth Bloomfield, Julian Beach, Kristen Dahlgren, Nick K Davis, Elisa Fontana, Spyridon Gennatas, Qamar Ghafoor, Franck Housseau, Daniel Lubelski, Zhehao Zhang, Matt Hancock, William Ince, Dominic James, Sam Khan, Victoria Kunene, John McGrane, Gerard Cathal Millen, Benjamin Moxley-Wyles, David Narganes-Carlon, Miranda Payne, Paul J Ross, Rene Roux, Michael Rowe, Rebecca Lee, Jerry S H Lee, Justin K H Liu, Deepak Aggarwal, Aaron B S Teoh, Chrissie Thirlwell, Michael Tilby, Stefan Symeonides, Isabella Watts, David B Agus, Santa J Ono, Tim Elliott, Paul Calleja, Lennard Y W Lee
Published in
Frontiers in artificial intelligence. Volume 9. Pages 1796682. Epub Jun 03, 2026.
Abstract
Artificial intelligence (AI) has rapidly become the focal point of global governmental attention and investment. Nations are launching AI for science strategies on a scale comparable to historic endeavors such as Apollo and the Manhattan Project. These coordinated programs carry profound promise for people living with cancer, for those at risk of disease and for transformative public benefit. Central to this transformation is the rise of sovereign AI supercomputers which are fundamentally reshaping biomedical research. These publicly owned systems provide secure, large-scale computational capacity, enabling integration of complex health data and rapid analysis that was previously constrained. This review examines the geographic distribution, technical capabilities, and biomedical applications of these infrastructures. Key computational workloads that now benefit significantly from AI implementations include cancer imaging and diagnosis, personalized treatments, whole-genome and single-cell level analysis, and computational drug discovery. This approach has supercharged our efforts at the United Kingdom's Cancer Vaccine AI & Supercomputing Project, our flagship national initiative to create new AI foundation models to accelerate the development of tools to establish immunity from cancer. In addition, this review evaluates governance models that safeguard patient privacy and intellectual property as well as measures that promote international collaboration while preserving compliance with regional regulations and make safer, more precise and effective treatments for public benefit. Substantial challenges exist, however, including inequitable resource availability, heterogeneous data standards and regulatory frameworks, and unbalanced computational expertise impeding the effective use of sovereign compute. Global collaborations are key to providing equitable access to advanced analytics, shortening the path from bench to bedside, and developing critical innovative tools for people affected by cancer.
PMID:
42318580
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.
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