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The future of mathematical oncology in the age of AI
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  • Perspective
  • Open access
  • Published: 26 January 2026

The future of mathematical oncology in the age of AI

  • Russell C. Rockne1,
  • Morten Andersen2,
  • Alexander R. A. Anderson3,
  • David Basanta3,
  • Angela Bentivegna4,
  • Sebastien Benzekry5,
  • Sergio Branciamore1,
  • Sarah C. Brüningk6,7,
  • Martina Conte8,
  • Farnoush Farahpour9,10,
  • Aleksandra Karolak11,
  • Alvaro Köhn-Luque12,
  • Guillermo Lorenzo13,14,
  • Babgen Manookian1,
  • Andrei S. Rodin1,
  • Lara Schmalenstroer9,
  • Juan Soler15,
  • Cristian Tomasetti1 &
  • …
  • Konstancja Urbaniak1 

npj Systems Biology and Applications , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cancer
  • Computational biology and bioinformatics
  • Mathematics and computing

Abstract

This perspective article discusses emerging advances at the interface of mechanistic modeling and data-driven machine learning, highlighting opportunities for AI to accelerate discovery, improve predictive modeling, and enhance clinical decision-making. We address critical limitations of current AI approaches and propose a perspective on a future where AI augments mechanistic rigor, clinical relevance, and human creativity under the umbrella of a redefined understanding of Mathematical Oncology.

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Data availability

No datasets were generated or analysed during the current study.

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Acknowledgements

The authors acknowledge the generosity of the city of Ortigia, Syracuse, Sicily, for providing the meeting venue and refreshments and the Beckman Research Institute at City of Hope for financial support.

Author information

Authors and Affiliations

  1. Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA

    Russell C. Rockne, Sergio Branciamore, Babgen Manookian, Andrei S. Rodin, Cristian Tomasetti & Konstancja Urbaniak

  2. Centre for Mathematical Modeling - Human Health and Disease, Roskilde University, Roskilde, Denmark

    Morten Andersen

  3. Department of Integrated Mathematical Oncology, Moffitt Cancer Centre, Tampa, FL, USA

    Alexander R. A. Anderson & David Basanta

  4. School of Medicine and Surgery, University Milano-Bicocca, Italy; Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy

    Angela Bentivegna

  5. Centre Inria d’Université Côte d’Azur and Cancer Research Center of Marseille, Institut Paoli-Calmettes, Inserm, CNRS, Aix Marseille University, Marseille, France

    Sebastien Benzekry

  6. Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland

    Sarah C. Brüningk

  7. Department of Digital Medicine, University of Bern, Bern, Switzerland

    Sarah C. Brüningk

  8. Politecnico of Torino, Turin, Italy

    Martina Conte

  9. Group of Bioinformatics and Computational Biophysics, University of Duisburg-Essen, Essen, Germany

    Farnoush Farahpour & Lara Schmalenstroer

  10. Institute for Cell Biology (Cancer Research), University Hospital Essen, Essen, Germany

    Farnoush Farahpour

  11. Department of Machine Learning, Moffitt Cancer Centre, Florida, USA

    Aleksandra Karolak

  12. Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Norway and Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    Alvaro Köhn-Luque

  13. Group of Numerical Methods in Engineering, Department of Mathematics and CITEEC, University of A Coruña, A Coruña, Spain

    Guillermo Lorenzo

  14. Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA

    Guillermo Lorenzo

  15. Department of Applied Mathematics and Research Unit Modeling Nature (MNat). University of Granada, Granada, Spain

    Juan Soler

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Contributions

R.C.R. attended the meeting in Syracuse and contributed to and approved the final manuscript. M.A. attended the meeting in Syracuse and contributed to and approved the final manuscript. A.R.A.A. attended the meeting in Syracuse and contributed to and approved the final manuscript. D.B. attended the meeting in Syracuse and contributed to and approved the final manuscript. A.B. attended the meeting in Syracuse and contributed to and approved the final manuscript. S.Be. attended the meeting in Syracuse and contributed to and approved the final manuscript. S.Br. attended the meeting in Syracuse and contributed to and approved the final manuscript. S.C.Bru. attended the meeting in Syracuse and contributed to and approved the final manuscript. M.C. attended the meeting in Syracuse and contributed to and approved the final manuscript. F.F. attended the meeting in Syracuse and contributed to and approved the final manuscript. A.K. attended the meeting in Syracuse and contributed to and approved the final manuscript. A.K.-L. attended the meeting in Syracuse and contributed to and approved the final manuscript. G.L. attended the meeting in Syracuse and contributed to and approved the final manuscript. B.M. attended the meeting in Syracuse and contributed to and approved the final manuscript. A.S.R. contributed to and approved the final manuscript. L.S. attended the meeting in Syracuse and contributed to and approved the final manuscript. J.S. attended the meeting in Syracuse and contributed to and approved the final manuscript. C.T. attended the meeting in Syracuse and contributed to and approved the final manuscript. K.U. attended the meeting in Syracuse and contributed to and approved the final manuscript. All authors read and approved the manuscript.

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Correspondence to Russell C. Rockne.

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Rockne, R.C., Andersen, M., Anderson, A.R.A. et al. The future of mathematical oncology in the age of AI. npj Syst Biol Appl (2026). https://doi.org/10.1038/s41540-026-00656-9

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  • Received: 30 September 2025

  • Accepted: 19 January 2026

  • Published: 26 January 2026

  • DOI: https://doi.org/10.1038/s41540-026-00656-9

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