Modeling of innate immune responses of cells for vaccine production

The virus replication in vitro, in particular in bioreactors, for vaccine production (for instance influenza A virus) has been previously studied using a distributed population balance model (Sidorenko et al., 2008). The solution of such models can be obtained with kinetic Monte Carlo simulations. Here we extend the previous model structure in two ways. First we replace the constant infection reaction constant by a function taking into account the heterogeneity of cells in a typical bioreactor environment. Second, we take into account the observed response of a cell to a virus attack, an immune response of the system. The immune response in a bioreactor can be related to the production of a signal protein like an interferon. Parallel to the cell dynamics also the interferon concentration will be modeled. We will study this as an additional parameter playing an important role for the infection probability. The dynamical evolution of the cell population, the total virus number via replication, and its dependency on the initial conditions will be studied here. It can be shown that the extended model can be used to improve experimental data interpretation in several ways. The previous artificial introduction of a time lag is no longer necessary in the proposed model. Also different scenarios of virus replication with low and high yield can now be interpreted consistently within one model approach.