A Mathematical Framework for Enhanced Cancer Eradication Using DNBT-CureX Nanocomplex: Integrating Nanotechnology, siRNA, and STING Agonists with Advanced Modeling

This conceptual paper presents a rigorous mathematical framework for DNBT-CureX, a hypothetical nanocomplex designed to achieve asymptotic tumor extinction in cancer by integrating doxorubicin, siRNA, and STING agonists within a nanoparticle delivery system. Drawing from pharmacodynamics, pharmacokinetics, gene expression dynamics, and immuno-oncology, the model employs a system of ordinary differential equations (ODEs) to describe drug distribution, release, cellular interactions, and tumor eradication. Enhancements include detailed toxicity modeling for healthy cells, drug resistance dynamics mitigated by siRNA, nanoparticle clearance by the reticuloendothelial system (RES), detailed modeling of cancer stem cells (CSCs) with expanded dynamics including quiescence and niche interactions, refined immune response modeling with expanded details on specific immune cells (e.g., macrophages \( M_\phi \), NK cells \( NK \), dendritic cells \( DC \), CD4+ helper T cells \( Th \), CD8+ cytotoxic T cells \( Tc \), and B cells \( B \) for antibody production), specific adaptations for immunity in solid tumors with hypoxia-induced suppression, modeling of hematological tumors, and a section for brain tumors considering the blood-brain barrier (BBB) and glioma-specific dynamics. We derive analytical approximations, perform numerical simulations using Python, and incorporate sensitivity analysis, quantitative statistics, Bayesian inference, uncertainty quantification, and falsifiability assessments. Supported by real-world data analogies from literature and reproducible code, the framework demonstrates asymptotic tumor extinction under optimized parameters while preserving healthy tissue. While theoretical, this model provides a blueprint for future empirical validation in nanomedicine and precision oncology.