<p>This paper proposes a robust nonlinear chemotherapy control framework for brain tumor treatment based on a barrier-function super-twisting sliding mode control (BF–STSMC) strategy. The controller is designed for a targeted tumor–immune–drug interaction model that explicitly incorporates drug selectivity and tumor-dependent drug-binding dynamics. To enhance control performance and eliminate manual gain tuning, the red fox optimization (RFO) algorithm is employed to automatically optimize the controller parameters. A Lyapunov-based stability analysis establishes finite-time convergence and closed-loop robustness in the presence of system nonlinearities and parametric uncertainties. Numerical simulation results demonstrate that the proposed approach achieves rapid and complete tumor suppression, improved preservation of healthy and immune cell populations, and bounded, safety-compliant drug infusion profiles, outperforming conventional super-twisting sliding mode chemotherapy control schemes.</p>