Modeling control with uncertainty of immune response basis on clinical data

The aim of this work is to numerically solve a problem of control with uncertainty of the immune response. The problem of control is described by a system of nonlinear ordinary differential equations with a retarded argument. Control with uncertainty implies that the parameter values are unknown and parameter estimation is adjusted as new laboratory data becomes available. The paper considers immune responses in acute pneumonia and viral hepatitis B. The treatment programs based on immunotherapy which consists in introduction of prepared immunoglobulins or donor antibodies are constructed. Presented results are based on the actual clinical data.