Optimal control of combination immunotherapy in a glioblastoma-immune dynamics model DOI Creative Commons
Hannah G. Anderson, Gregory P. Takacs, Jeffrey K. Harrison

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 2, 2024

Abstract The immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain glioblastoma. However, when conjunction with CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 shown efficacy preclinical studies. In this paper, we aim to optimize treatment regimens combination immunotherapy using optimal control theory. We extend treatment-free glioblastoma-immune dynamics ODE model include interventions and CCR2 antagonist. An optimized regimen increases survival of an average mouse from 32 days post-tumor implantation without 111 treatment. scale approach virtual murine cohort evaluate mortality quality life concerns during treatment, predict survival, tumor recurrence, or death after A parameter identifiability analysis identifies five parameters suitable personalizing within cohort. Sampling these practically identifiable reveals that personalized, enhance survival: 84% mice survive day 100, compared 60% previously studied experimental regimen. Subjects high growth rates low T cell kill are identified more likely die due their compromised systems tumors. Notably, MDSC rate emerges long-term predictor either disease-free death. Highlights mathematical glioma-immune integrates immunotherapy. extends by 79 days. Quality outcomes were evaluated myeloid-derived suppressor cells predicts survival.

Language: Английский

Next-Generation Vaccines: Leveraging Deep Learning for Predictive Immune Response and Optimal Vaccine Design DOI

K. R. Saranya,

J. L.,

P. Valarmathi

et al.

Journal of Machine and Computing, Journal Year: 2025, Volume and Issue: unknown, P. 768 - 788

Published: April 5, 2025

The rapid advancement in vaccine development has become increasingly critical addressing global health challenges, particularly the wake of emerging infectious diseases. Traditional methods design, while effective, often involve lengthy processes trial and error, which can delay deployment life-saving immunizations. In pursuit enhancing efficacy, application deep learning techniques emerged as a transformative approach. This study presents implementation an Integrated Neural Network Model (INNM), synergistically combines Artificial Networks (ANNs) Random Forests for predictive immune response optimal design. INNM employs hybrid feature selection methodology, integrating Pearson correlation with Recursive Feature Elimination (RFE), to identify most relevant immunological predictors. Implemented Jupyter Notebook environment, model achieved impressive accuracy rate 98.4%, demonstrating its potential revolutionize development. innovative approach underscores capability predict responses high precision, paving way next generation vaccines.

Language: Английский

Citations

0
Thromboembolic and bleeding events associated with angiogenesis inhibitors in cancer patients DOI
Zhuo Ma, Yi Zhang, Dan Sun

et al.

Expert Opinion on Drug Safety, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Angiogenesis inhibitors are associated with increased risk of thromboembolic events (TEEs) and hemorrhagic events. However, their clinical features not well characterized in real-world studies. First, we conducted a pharmacovigilance study to investigate characteristics TEEs bleeding compare vascular endothelial growth factor its receptor (VEGF/VEGFRIs) other antiangiogenic agents. Second, performed retrospective analysis lung cancer patients who received bevacizumab or anlotinib assess the incidence VEGF/VEGFRI-associated bleeding. In study, both VEGF/VEGFR-targeted biologics VEGFR-tyrosine kinase were higher reporting arterial thromboembolism (ATE) (reporting odd ratio (ROR) 2.91; ROR 1.25; respectively), (ROR 2.56; 2.35; respectively). Venous (VTE) was only 3.11). cohort bevacizumab, aflibercept, ramucirumab showed strongest associations VTE, ATE, bleeding, respectively. 261 treated anlotinib, 42.9% older than 65 years, 62.1% male, occurred 11.5%, 8.8%. All VEGF/VEGFRIs ATE risk. also significantly raise VTE.

Language: Английский

Citations

0
Optimal control of combination immunotherapy for a virtual murine cohort in a glioblastoma-immune dynamics model DOI Creative Commons

Hannah G Anderson,

Gregory P. Takacs, Jeffrey K. Harrison

et al.

Journal of Theoretical Biology, Journal Year: 2024, Volume and Issue: unknown, P. 111951 - 111951

Published: Sept. 1, 2024

Language: Английский

Citations

0
Optimal control of combination immunotherapy in a glioblastoma-immune dynamics model DOI Creative Commons
Hannah G. Anderson, Gregory P. Takacs, Jeffrey K. Harrison

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 2, 2024

Abstract The immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain glioblastoma. However, when conjunction with CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 shown efficacy preclinical studies. In this paper, we aim to optimize treatment regimens combination immunotherapy using optimal control theory. We extend treatment-free glioblastoma-immune dynamics ODE model include interventions and CCR2 antagonist. An optimized regimen increases survival of an average mouse from 32 days post-tumor implantation without 111 treatment. scale approach virtual murine cohort evaluate mortality quality life concerns during treatment, predict survival, tumor recurrence, or death after A parameter identifiability analysis identifies five parameters suitable personalizing within cohort. Sampling these practically identifiable reveals that personalized, enhance survival: 84% mice survive day 100, compared 60% previously studied experimental regimen. Subjects high growth rates low T cell kill are identified more likely die due their compromised systems tumors. Notably, MDSC rate emerges long-term predictor either disease-free death. Highlights mathematical glioma-immune integrates immunotherapy. extends by 79 days. Quality outcomes were evaluated myeloid-derived suppressor cells predicts survival.

Language: Английский

Citations

0