STOCHASTIC OPTIMAL ENHANCEMENT OF IMMUNE RESPONSE

摘要

Therapeutic enhancement of innate immune response to microbial attack is addressed as the optimal control of a dynamic system. Without therapy, the modeled response depends upon the initial concentration of pathogens in the simulated attack. Immune response can be augmented by therapeutic agents that kill the pathogen directly, that stimulate the production of plasma cells or antibodies, or that enhance organ health. Previous papers demonstrated open- and closed-loop optimal control solutions that defeat the pathogen and preserve organ health, given initial conditions that otherwise would be lethal Therapies based on separate and combined application of the agents were derived by minimizing a quadratic cost function that weighted both system response and control usage, providing implicit control over harmful side effects. We focus on the effects that corrupted or incomplete measurements may have on the effectiveness of neighboring-optimal feedback control, which combines the open-and closed-loop control. We show the number of measurements that provide complete observability of the perturbed state, as well as the impact of imperfect measurements on therapy. We conclude that effective therapy can be obtained over a broad range of uncertainty in initial conditions, disturbance inputs, or feedback measurements.