Entropy-driven Effective Tumor Detection using Nanoscale Medical Agents

Despite advances in medical research and therapy, cancer remains a major global health issue due to its complexity in treatment. Depending on the type and extent of the disease, tumor removal with cancer treatment drugs without harming surrounding healthy tissue is a critical challenge. The targeted drug delivery (TDD) approach has emerged to increase the effectiveness of treatment while reducing side effects. This paper envisions a hybrid navigation mechanism that utilizes chemotaxis and entropy to direct nanoscale medical agents (NMAs) toward cancerous cells within a tumor microenvironment (TME) to release medication and treat them. The NMAs sense the concentration gradient of the biomarkers in their vicinity to localize the tumor(s). For this study, we used hypoxia as our biomarker, given the higher oxygen consumption by cancerous cells. The numerical results show that the effectiveness and reliability of the hybrid navigation strategy are significantly higher than those of the random and chemotaxis navigation mechanisms. Furthermore, analysis of cancerous cell statistics over time demonstrates that the proposed method eliminates tumors faster than the other two strategies.