Evidence map›Paper›PMID 41588010›Full record

ReviewNPJ systems biology and applications2026

The future of mathematical oncology in the age of AI.

Russell C Rockne, Morten Andersen, Alexander R A Anderson, David Basanta, Angela Bentivegna, Sebastien Benzekry, Sergio Branciamore, Sarah C Brüningk, Martina Conte, Farnoush Farahpour and 9 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ systems biology and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. The future of mathematical oncology in the age of AI.NPJ systems biology and applications · 2026
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Russell C RockneDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA. rrockne@coh.org.
Morten AndersenCentre for Mathematical Modeling - Human Health and Disease, Roskilde University, Roskilde, Denmark.
Alexander R A AndersonDepartment of Integrated Mathematical Oncology, Moffitt Cancer Centre, Tampa, FL, USA.
David BasantaDepartment of Integrated Mathematical Oncology, Moffitt Cancer Centre, Tampa, FL, USA.
Angela BentivegnaSchool of Medicine and Surgery, University Milano-Bicocca, Italy; Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy.
Sebastien BenzekryCentre Inria d'Université Côte d'Azur and Cancer Research Center of Marseille, Institut Paoli-Calmettes, Inserm, CNRS, Aix Marseille University, Marseille, France.
Sergio BranciamoreDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA.
Sarah C BrüningkDepartment of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland.
Martina ContePolitecnico of Torino, Turin, Italy.
Farnoush FarahpourGroup of Bioinformatics and Computational Biophysics, University of Duisburg-Essen, Essen, Germany.
Aleksandra KarolakDepartment of Machine Learning, Moffitt Cancer Centre, Florida, USA.
Alvaro Köhn-LuqueOslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Norway and Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.
Guillermo LorenzoGroup of Numerical Methods in Engineering, Department of Mathematics and CITEEC, University of A Coruña, A Coruña, Spain.
Babgen ManookianDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA.
Andrei S RodinDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA.
Lara SchmalenstroerGroup of Bioinformatics and Computational Biophysics, University of Duisburg-Essen, Essen, Germany.
Juan SolerDepartment of Applied Mathematics and Research Unit Modeling Nature (MNat). University of Granada, Granada, Spain.
Cristian TomasettiDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA.
Konstancja UrbaniakDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, CA, USA.

Funding

The Delta Ecology of NSCLC TreatmentU54CA274507 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI Alexander Robertson Allan Anderson, ROBERT A GATENBY · 2023 to 2026
$9.4M
NCI NIH HHS U54 CA274507
6 · The paper itself

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.

Indexed as

Artificial IntelligenceMedical OncologyComputational BiologyData AnalyticsHumansMachine LearningNeoplasmsPredictive Learning ModelsSoft Computing

Identifiers

PMID41588010
PMCPMC12890909

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.