ReviewJournal of the Royal Society, Interface2018
Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues.
Review in Journal of the Royal Society, Interface, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
60 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Toward Personalized Computer Simulation of Breast Cancer Treatment: A Multiscale Pharmacokinetic and Pharmacodynamic Model Informed by Multitype Patient Data.Cancer research · 2019Trial
- Tumor organoids modeling reveals timed responses and interplay of radiotherapy and chemotherapy in pancreatic cancer.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2026Article
- Continuous adaptive chemotherapy dosing by using planet-formation-inspired dynamics: analytical andFrontiers in oncology · 2026Article
- Rules of life at the interface of calcium signaling and mechanobiology.APL bioengineering · 2025Review
- A consensus statement on the use of digital twins in medicine.NPJ digital medicine · 2025Article
- Ultrasmall nanoparticles for co-delivery of antisense oligonucleotides targeting miR-21 and miR-210 to treat glioblastoma.Journal of nanobiotechnology · 2025Article
- Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition.Journal of computational science · 2024Article
- Nanofunctionalized Microparticles for Glucose Delivery in Three-Dimensional Cell Assemblies.ACS applied materials & interfaces · 2024Article
- The reprotoxic adverse side effects of neurogenic and neuroprotective drugs: current use of human organoid modeling as a potential alternative to preclinical models.Frontiers in pharmacology · 2024Review
- Article
- An in silico model of the capturing of magnetic nanoparticles in tumour spheroids in the presence of flow.Biomedical microdevices · 2023Article
- Dynamics of Fibril Collagen Remodeling by Tumor Cells: A Model of Tumor-Associated Collagen Signatures.Cells · 2023Article
- Treatment of evolving cancers will require dynamic decision support.Annals of oncology : official journal of the European Society for Medical Oncology · 2023Review
- Data-driven spatio-temporal modelling of glioblastoma.Royal Society open science · 2023Review
- Digital twin demonstrates significance of biomechanical growth control in liver regeneration after partial hepatectomy.iScience · 2023Article
- Article
- Systems bioengineering approaches for developmental toxicology.Computational and structural biotechnology journal · 2023Review
- Hybrid computational models of multicellular tumour growth considering glucose metabolism.Computational and structural biotechnology journal · 2023Review
- Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse.iScience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these
Indexed as
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What OpenQuestion holds
Registered trials
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.