A Hierarchical Framework for Autonomous Macrophage Migration Based on Exploration and Exploitation

Background: Macrophage migration is vital in cancer therapy, as it contributes to the elimination of cancer cells and enables targeted drug delivery. However, the natural migratory ability of macrophage is limited, and the location of cancer cells are dynamic and uncertain. Methods: To address this issue, we propose a hierarchical framework based on exploration and exploitation to enable autonomous macrophage migration. Specifically, the upper layer employs a particle filter to explore cancer cell location by sensing signaling molecule concentrations. This information is then passed to the middle layer, which applies the maximum Shannon entropy sampling principle to determine the optimal movement position. Finally, the lower layer utilizes optogenetics to guide migration toward targets, which constitutes exploitation. The interaction among the layers enables autonomous macrophage migration. Results: Simulation results verify the effectiveness of the proposed framework, demonstrating that the macrophage successfully eliminates the cancer cell even when the target location is unknown. Furthermore, the results reveal that the proposed framework achieves higher targeting precision compared to both greedy and nonlayered strategies, thereby enhancing the accuracy of cancer cell elimination and targeted drug delivery. Conclusions: This study highlights the potential translational value for improving targeted cancer therapy.