Combined Application of CAR-T Cells and Chlorambucil for CLL Treatment: Insights from Nonlinear Dynamical Systems and Model-Based Design for Dose Finding

Abstract

Background: This work presents a mechanistic nonlinear model, formulated as a system of first-order Ordinary Differential Equations, to investigate the dynamics of Chronic Lymphocytic Leukemia (CLL) under combined chemoimmunotherapy using CAR-T cells and chlorambucil. Methods: Leveraging nonlinear dynamical systems theory and a model-based design approach, we derive optimal dosing strategies through extensive in silico simulations, providing hemato-oncologists with actionable tools to refine CLL treatment. The model captures the short- and long-term impacts of both therapies on leukemia cell populations, enabling precise predictions of therapeutic outcomes. Results: By analyzing local and global system dynamics, we establish sufficient conditions for dosing and protocol design, offering a framework to optimize therapies based on individual patient responses. Comparisons of dose-escalation and -de-escalation strategies further demonstrate potential trajectories, such as complete eradication, partial response, or relapse, providing data-driven guidance for improving patient care. Conclusions: This study highlights the power of mathematical modeling in blood cancer research, enhancing the development of personalized and effective CLL treatment regimens.

Keywords

• asymptotic stability
• cancer
• CAR-T cells
• chlorambucil
• dose-finding
• in silico