Study of intracellular signaling processes might provide invaluable insight into the development of new targeted anticancer therapies. However the complexity of signaling mechanisms requires sophisticated mathematical models in order to create a close representation of the processes involved. In order to aid this task we created a new application - Solvary that simplifies the evaluation of deterministic and stochastic models of the intracellular processes. The simulations are carried out using either stochastic or deterministic methods or a new method which combines those two approaches, if some of the model variables are marked as deterministic and some as stochastic. The usefulness of Solvary was evaluated trough a study of viability control processes in cancer cells. The study is based on a complex model of p53 pathway build of over 40 nonlinear, differential equations and 10 reaction propensities for stochastic variables such as genes state. By controlling the level of either Mdm2 or IkBa trough RNA interference we show in silico how cellular viability can be reduced to the level specified by the biological experiments.
