ArticleJournal of theoretical biology2018
Pharmacokinetic/pharmacodynamic modeling of combination-chemotherapy for lung cancer.
Article in Journal of theoretical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Optimizing the Efficacy of Vaccine-Induced Immunotherapy in Melanomas.Bulletin of mathematical biology · 2025Article
- Optimizing cancer therapy: a review of the multifaceted effects of metronomic chemotherapy.Frontiers in cell and developmental biology · 2024Review
- Evaluation of Lung Cancer Patient Response to First-Line Chemotherapy by Integration of Tumor Core Biopsy Metabolomics with Multiscale Modeling.Annals of biomedical engineering · 2023Article
- Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data.Annals of biomedical engineering · 2022Article
- An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.Scientific reports · 2020Article
- A Minimal PKPD Interaction Model for Evaluating Synergy Effects of Combined NSCLC Therapies.Journal of clinical medicine · 2020Article
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
- Hybrid modeling frameworks of tumor development and treatment.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Pharmacokinetic/Pharmacodynamics Modeling of Drug-Loaded PLGA Nanoparticles Targeting Heterogeneously Vascularized Tumor Tissue.Pharmaceutical research · 2019Article
- Evaluation of Drug-Loaded Gold Nanoparticle Cytotoxicity as a Function of Tumor Vasculature-Induced Tissue Heterogeneity.Annals of biomedical engineering · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Chemotherapy for non-small cell lung cancer (NSCLC) typically involves a doublet regimen for a number of cycles. For any particular patient, a course of treatment is usually chosen from a large number of combinational protocols with drugs in concomitant or sequential administration. In spite of newer drugs and protocols, half of patients with early disease will live less than five years and 95% of those with advanced disease survive for less than one year. Here, we apply mathematical modeling to simulate tumor response to multiple drug regimens, with the capability to assess maximum tolerated dose (MTD) as well as metronomic drug administration. We couple pharmacokinetic-pharmacodynamic intracellular multi-compartment models with a model of vascularized tumor growth, setting input parameters from in vitro data, and using the models to project potential response in vivo. This represents an initial step towards the development of a comprehensive virtual system to evaluate tumor response to combinatorial drug regimens, with the goal to more efficiently identify optimal course of treatment with patient tumor-specific data. We evaluate cisplatin and gemcitabine with clinically-relevant dosages, and simulate four treatment NSCLC scenarios combining MTD and metronomic therapy. This work thus establishes a framework for systematic evaluation of tumor response to combination chemotherapy. The results with the chosen parameter set indicate that although a metronomic regimen may provide advantage over MTD, the combination of these regimens may not necessarily offer improved response. Future model evaluation of chemotherapy possibilities may help to assess their potential value to obtain sustained NSCLC regression for particular patients, with the ultimate goal of optimizing multiple-drug chemotherapy regimens in clinical practice.
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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.