ArticleScientific reports2017
A Predictive Mathematical Modeling Approach for the Study of Doxorubicin Treatment in Triple Negative Breast Cancer.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
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Who cites it
34 citing papers in PubMed, 55 citations in OpenAlex.
- Exploiting the dynamics of hyperthermia-enhanced delivery of thermosensitive liposomal doxorubicin to solid tumors.Drug delivery · 2026Article
- Representation meets optimization: Training PINNs and PIKANs for gray-box discovery in systems pharmacology.Computers in biology and medicine · 2026Article
- Personalizing neoadjuvant chemotherapy regimens for triple-negative breast cancer using a biology-based digital twin.NPJ systems biology and applications · 2025Article
- Gene expression and agent-based modeling improve precision prognosis in breast cancer.Scientific reports · 2025Article
- Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.Nature reviews. Cancer · 2025Review
- Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacology.ArXiv · 2025Article
- Learning Chemotherapy Drug Action via Universal Physics-Informed Neural Networks.Pharmaceutical research · 2025Article
- Doxorubicin PK/PD modeling in multiple myeloma: towards in silico trials.Biology direct · 2025Article
- Subcellular Organelle Targeting as a Novel Approach to Combat Tumor Metastasis.Pharmaceutics · 2025Review
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- A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin.Cancer biology & therapy · 2024Article
- Complex Interplay between DNA Damage and Autophagy in Disease and Therapy.Biomolecules · 2024Review
- A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data.Engineering with computers · 2024Article
- Analysis and modeling of cancer drug responses using cell cycle phase-specific rate effects.Nature communications · 2023Article
- A Mathematical Model of In Vitro Cellular Uptake of Zoledronic Acid and Isopentenyl Pyrophosphate Accumulation.Pharmaceutics · 2022Article
- Combined effects of pioglitazone and doxorubicin on migration and invasion of MDA-MB-231 breast cancer cells.Journal of the Egyptian National Cancer Institute · 2022Article
- Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules.PLoS computational biology · 2022Article
- Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin.Frontiers in molecular biosciences · 2022Article
- A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.Journal of personalized medicine · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Doxorubicin forms the basis of chemotherapy regimens for several malignancies, including triple negative breast cancer (TNBC). Here, we present a coupled experimental/modeling approach to establish an in vitro pharmacokinetic/pharmacodynamic model to describe how the concentration and duration of doxorubicin therapy shape subsequent cell population dynamics. This work features a series of longitudinal fluorescence microscopy experiments that characterize (1) doxorubicin uptake dynamics in a panel of TNBC cell lines, and (2) cell population response to doxorubicin over 30 days. We propose a treatment response model, fully parameterized with experimental imaging data, to describe doxorubicin uptake and predict subsequent population dynamics. We found that a three compartment model can describe doxorubicin pharmacokinetics, and pharmacokinetic parameters vary significantly among the cell lines investigated. The proposed model effectively captures population dynamics and translates well to a predictive framework. In a representative cell line (SUM-149PT) treated for 12 hours with doxorubicin, the mean percent errors of the best-fit and predicted models were 14% (±10%) and 16% (±12%), which are notable considering these statistics represent errors over 30 days following treatment. More generally, this work provides both a template for studies quantitatively investigating treatment response and a scalable approach toward predictions of tumor response in vivo.
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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.