ArticlePLoS computational biology2023
Mathematical modeling of intratumoral immunotherapy yields strategies to improve the treatment outcomes.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 13 citations in OpenAlex.
- Mechanistic modeling of tumor immune microenvironment reveals strategies to enhance antibody-drug conjugates' efficacy.Journal for immunotherapy of cancer · 2026Article
- Fracking in Tumors: A Key Drug Transport Mechanism.Annals of biomedical engineering · 2026Article
- Mapping radiosensitivity in glioblastoma using MR elastography and biomechanical modeling.Scientific reports · 2026Article
- A multiphysics computational model of focused ultrasound-enhanced drug delivery using temperature-sensitive liposomes.Biomechanics and modeling in mechanobiology · 2026Article
- Review
- Advances in intratumoral immunotherapy from a neuro-immune-endocrine perspective for breast cancer treatment.Frontiers in oncology · 2026Review
- Optimizing therapeutic outcomes with Mechanotherapy and Ultrasound Sonopermeation in solid tumors.PLoS computational biology · 2025Article
- Mathematical Modeling ofBioengineering (Basel, Switzerland) · 2025Article
- Multi-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion.PLoS computational biology · 2025Article
- Challenges and opportunities for the next generation of computational tumor models.PLoS biology · 2025Article
- Biomarkers of mRNA vaccine efficacy derived from mechanistic modeling of tumor-immune interactions.PLoS computational biology · 2025Article
- Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.Nature reviews. Cancer · 2025Review
- Synergistic mechanotherapy and sonopermeation guided by mathematical modeling for solid tumor treatment.Frontiers in drug delivery · 2025Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Intratumoral injection of immunotherapy aims to maximize its activity within the tumor. However, cytokines are cleared via tumor vessels and escape from the tumor periphery into the host-tissue, reducing efficacy and causing toxicity. Thus, understanding the determinants of the tumor and immune response to intratumoral immunotherapy should lead to better treatment outcomes. In this study, we developed a mechanistic mathematical model to determine the efficacy of intratumorally-injected conjugated-cytokines, accounting for properties of the tumor microenvironment and the conjugated-cytokines. The model explicitly incorporates i) the tumor vascular density and permeability and the tumor hydraulic conductivity, ii) conjugated-cytokines size and binding affinity as well as their clearance via the blood vessels and the surrounding tissue, and iii) immune cells-cancer cells interactions. Model simulations show how the properties of the tumor and of the conjugated-cytokines determine treatment outcomes and how selection of proper parameters can optimize therapy. A high tumor tissue hydraulic permeability allows for the uniform distribution of the cytokines into the tumor, whereas uniform tumor perfusion is required for sufficient access and activation of immune cells. The permeability of the tumor vessels affects the blood clearance of the cytokines and optimal values depend on the size of the conjugates. A size >5 nm in radius was found to be optimal, whereas the binding of conjugates should be high enough to prevent clearance from the tumor into the surrounding tissue. In conclusion, development of strategies to improve vessel perfusion and tissue hydraulic conductivity by reprogramming the microenvironment along with optimal design of conjugated-cytokines can enhance intratumoral immunotherapy.
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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.