We constructed deterministic and stochastic models to analyze both of our switches and developed two additional modeling approaches:

• a quantitative model based on the available experimental data;
• a new modeling algorithm, called C#Sim, based on object-oriented programming approach.

All models consistently demonstrate that:

• the mutual repressor switch is unlikely to exhibit bistability in a realistic experimental setting using monomeric transcription factors;
• the positive feedback loop switch is, in terms of robustness, far superior to the mutual repressor switch based on non-cooperative orthogonal DNA-binding domains of transcription factors, exhibiting bistability in more demanding (non-ideal) conditions.

Therefore, we predicted that the mutual repressor switch would not exhibit bistable behavior, while the positive feedback loop switch should be stable. These assessments were confirmed by experimental results, with the positive feedback loop switch clearly exhibiting bistability.

We also built a pharmacokinetic model of drug distribution to compare our mammalian cell-based therapy with the standard therapy.