This model accounts for cell fate decision network in the AGS gastric cancer cell line. A set of logical equations has been defined, wich recapitulates AGS data observed in cells in their baseline proliferative state. Using the modeling software GINsim, model reduction and simulation compression techniques were applied to cope with the vast state space of large logical models and enable simulations of pairwise applications of specific signaling inhibitory chemical substances. These simulations predicted synergistic growth inhibitory action of five combinations from a total of 21 possible pairs. All predicted non synergic pairs and four of the predicted synergic ones were confirmed in AGS cell growth real-time assays, including known synergic effects of MEK-AKT or MEK-PI3K inhibitions, along with novel synergistic effects of combined TAK1-AKT or TAK1-PI3K inhibitions.