Distribution of drugs through tissue is very important for the effective therapy. We built pharmacokinetic models to simulate distribution of biological drugs produced by the engineered microencapsulated cells for implantation into the liver to treat hepatitis C and into the muscle tissue for the therapy of myocardial ischemia in comparison to the standard therapy.

Pharmacokinetic models suggest that the proposed type of delivery should decrease the systemic side effects and the required dose of biological drugs.

Mathematical modeling was used to simulate different types of epigenetic switches (mutual repressor switch, based on the classical toggle switch and its extended version with introduction of additional positive feedback loops), where experimental parameters were incorporated into the model and modeling led to some unintuitive results on the introduction of non-linearity into the system, which was verified by experimental results.

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.