Evidence map›Paper›PMID 41085839›Full record

ArticleBulletin of mathematical biology2025

Optimal Control in Combination Therapy for Heterogeneous Cell Populations with Drug Synergies.

Simon F Martina-Perez, Samuel W S Johnson, Rebecca M Crossley, Jennifer C Kasemeier, Paul M Kulesa, Ruth E Baker

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Simon F Martina-PerezSchool of Medicine and Biomedical Sciences, University of Oxford, Oxford, UK. simon.martina-perez@medschool.ox.ac.uk.
Samuel W S JohnsonMathematical Institute, University of Oxford, Oxford, UK.
Rebecca M CrossleyMathematical Institute, University of Oxford, Oxford, UK. rebecca.crossley@maths.ox.ac.uk.ORCID http://orcid.org/0000-0001-7342-0207
Jennifer C KasemeierChildren's Mercy Hospital Research Institute, Kansas City, MO, USA.
Paul M KulesaChildren's Mercy Hospital Research Institute, Kansas City, MO, USA.
Ruth E BakerMathematical Institute, University of Oxford, Oxford, UK.

Funding

Engineering and Physical Sciences Research Council EP/T517811/1
6 · The paper itself

Abstract

Cell heterogeneity plays an important role in patient responses to drug treatments. In many cancers, it is associated with poor treatment outcomes. Many modern drug combination therapies aim to exploit cell heterogeneity, but determining how to optimise responses from heterogeneous cell populations while accounting for multi-drug synergies remains a challenge. In this work, we introduce and analyse a general optimal control framework that can be used to model the treatment response of multiple cell populations that are treated with multiple drugs that mutually interact. In this framework, we model the effect of multiple drugs on the cell populations using a system of coupled semi-linear ordinary differential equations and derive general results for the optimal solutions. We then apply this framework to three canonical examples and discuss the wider question of how to relate mathematical optimality to clinically observable outcomes, introducing a systematic approach to propose qualitatively different classes of drug dosing inspired by optimal control.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsModels, BiologicalNeoplasmsComputer SimulationDrug SynergismHumansMathematical Concepts

Identifiers

PMID41085839
PMCPMC12521341

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Registered trials

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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.