An adaptive control scheme for Interleukin-2 therapy

Abstract

Regulatory T cells (Treg) are suppressor cells that control self-reactive and excessive effector conventional helper T cell (Tconv) responses. Breakdown of the balance between Tregs and Tconvs is a hallmark of autoimmune and inflammatory diseases. Due to the positive dependency of both populations on Interleukin-2 (IL-2), it is subtle leverage to restore the healthy immune balance. By employing a mechanistic mathematical model, we studied the IL-2 therapy in order to increase and stabilize Treg population and restrict inflammatory Tconv response. We introduced an adaptive control strategy to design the minimal IL-2 dosage. This adaptive strategy allows for an individualized therapy based on the feedback of immune kinetics of the patient. Our in silico results suggest that a minimal Treg population is required to restrict the transient side-effect of IL-2 injections on the effector Tconv response. The combination of IL-2 and adoptive Treg transfer therapies is able to limit this side effect in our simulations. Implications of our in silico results are discussed in the context of autoimmunity and transplantation.