Optimizing Hyperthermia-Mediated Drug Delivery for Hepatocellular Carcinoma: A Multi-Objective Genetic Algorithm Approach

This study explores the optimization of hyperthermia-mediated drug delivery using thermo-sensitive liposomes (TSLs) for treating hepatocellular carcinoma (HCC). By employing a Multi-Objective Genetic Algorithm (MOGA), the research aims to maximize tumor cell kill rates while minimizing thermal damage to tissues. The mathematical models used include the Pennes' bioheat equation and drug diffusion equations, integrated into finite element simulations. The optimization process balances critical parameters which drive both heating protocol and drug release mechanisms, resulting in improved therapeutic outcomes. This innovative approach addresses the challenges of effective TSL-mediated chemotherapy, providing a promising pathway for enhancing clinical treatments of HCC.Clinical Relevance- This study is significant for clinicians as it proposes a computational method to obtain optimized input protocols for hyperthermia-mediated drug delivery in HCC. By fine-tuning treatment parameters, the approach aims to increase drug efficacy while reducing side effects, offering a more targeted and efficient alternative to conventional chemotherapy.