Cellular Automata Model of Drug Therapy for HIV Infection

In this study, we employ non-uniform Cellular Automata (CA) to simulate drug treatment of HIV infection, where each computational domain may contain different CA rules, in contrast to normal uniform CA models. Ordinary (or partial) differential equation models are insufficient to describe the two extreme time scales involved in HIV infection (days and decades), as well as the implicit spatial heterogeneity [4,3, 10]. R.M. Zorzenon dos Santose [13] (2001) reported a cellular automata approach to simulate three-phase patterns of human immunodeficiency virus (HIV) infection consistingof primary response, clinical latency and onset of acquired immunodeficiency syndrome (AIDS), Here we report a related model. We developed a non-uniform CA model to study the dynamics of drug therapy of HIV infection, which simulates four- phases (acute, chronic, drug treatment responds and onset of AIDS). Our results indicate that both simulations (with and without treatments) evolve to the relatively same steady state (characteristic of Wolfram's class II behaviour). Three different drugtherapies (mono-therapy, combined drug therapy and highly active antiretroviral therapy HAART) can also be simulated in our model. Our model for prediction of the temporal behaviour of the immune system to drug therapy qualitatively corresponds to clinical data.