Evidence map›Paper›PMID 40975428›Full record

ArticleJournal of theoretical biology2026

Drug-loaded nanoparticles for cancer therapy: A high-throughput multicellular agent-based modeling study.

Yafei Wang, John Metzcar, Elmar Bucher, Heber L Rocha, Vikram Jadhao, Randy Heiland, Hermann B Frieboes, Paul Macklin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of theoretical biology, 2026. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Yafei WangDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
John MetzcarDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
Elmar BucherDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
Heber L RochaDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
Vikram JadhaoDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
Randy HeilandDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA.
Hermann B FrieboesDepartment of Bioengineering, University of Louisville, Louisville, Kentucky, 40292, USA.
Paul MacklinDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, 47408, USA. Electronic address: macklinp@iu.edu.

Funding

Multiscale systems biology modeling to exploit tumor-stromal metabolic crosstalk in colorectal cancerU01CA232137 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FINLEY, STACEY DELERIA, MACKLIN, PAUL T · 2018 to 2022
$2.8M
(PQB6)An Integrative Computational and Bioengineered Tissue Model of MetastasisR01CA180149 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AGUS, DAVID B, ATALA, ANTHONY · 2013 to 2016
$2.3M
NCI NIH HHS R01 CA180149NCI NIH HHS U01 CA232137
6 · The paper itself

Abstract

Interactions between biological systems and engineered nanomaterials have become an important area of study due to their application in medicine. In particular, the opportunity to apply nanomaterials for cancer diagnosis and treatment presents a challenge due to the complex biology of this disease, which spans multiple time and spatial scales. A systems-level analysis from mathematical modeling and computational simulation to explore the interactions between anticancer drug-loaded nanoparticles (NPs), cells, and tissues, and the associated system parameters and patient response would be of benefit. Although a number of models have explored these interactions in the past, few have focused on simulating individual cell-NP interactions. This study develops a multicellular agent-based model of cancer nanotherapy that simulates NP internalization, drug release within the cell cytoplasm, inheritance of NPs by daughter cells at cell division, cell pharmacodynamic response to intracellular drug levels, and overall drug effect on tumor growth. A large-scale parallel computational framework is used to investigate the impact of pharmacokinetic design parameters (NP internalization rate, NP decay rate, anticancer drug release rate) and therapeutic strategies (NP doses and injection frequency) on tumor growth. In particular, through the exploration of NP inheritance at cell division, the results indicate that cancer treatment may be improved when NPs are inherited at cell division for cytotoxic chemotherapy. Moreover, smaller dose of cytostatic chemotherapy may also improve inhibition of tumor growth when cell division is not completely inhibited. This work suggests that slow delivery by heritable NPs can drive new dimensions of nanotherapy design for more sustained therapeutic response.

Indexed as

Antineoplastic AgentsModels, BiologicalNanoparticlesNeoplasmsComputer SimulationDrug Delivery SystemsHumansAntineoplastic AgentsAgent-based modelingAnticancer drug-loaded nanoparticlesCancer nanotherapyNanoparticle inheritance

Identifiers

PMID40975428
PMCPMC13006740

What Socratic holds

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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 Socratic graph.