Simulation of HIV-infection in artificial immune systems

Abstract Infection by the human immunodeficiency virus (HIV) causes a multi-faceted disease process which ultimately leads to severe degenerative conditions in the immune and nervous systems. The complexity of the virus/host-system interaction has brought into sharp focus the need for alternative efforts by which to overcome the limitations of available animal models. This article reports on the dynamics of HIV infection in an artificial immune system (AIS), a novel in silico tool for bio-medical research. Using a method of graphical programming, the HIV/AIS interactions are described at the cellular level and then transferred into the setting of an asynchronous cellular automaton simulation. A specific problem in HIV pathogenesis is addressed: To determine the extent by which the physiological connectivity of a normal B-cell, T-cell, macrophage immune system supports persistence of infection and disease progression to AIDS. Several observations are discussed which will be presented in four categories: (a) the major known manifestations of HIV infection and AIDS; (b) the predictability of latency and sudden progression to disease; (c) the predictability of HIV-dependent alterations of cytokine secretion patterns, and (d) secondary infections, which are found to be a critical element in establishing and maintaining a progressive disease dynamics. The effects of exogenously applied cytokine Interleukin 2 are considered. All results are summarized in a phase-graph model of the global HIV/AIS dynamical system.