Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection
Figure 5
Dynamics in fast virus growth models assuming that the internal equilibrium EI is (a) stable and (b) unstable.
(a) If the internal equilibrium is stable, then the dynamics can converge to this equilibrium via damped oscillation if the initial number of cancer cells is relatively low. On the other hand, if the initial number of cancer cells is relatively high, then uncontrolled cancer growth is observed. (b) If the internal equilibrium is unstable, then diverging oscillations are observed. Eventually, these diverging oscillations take the populations beyond the saddle node equilibrium, leading to unlimited cancer growth. Before that occurs, however, it is most likely that the cancer has been driven extinct in a stochastic setting because the diverging oscillations drive the tumor size to ever decreasing values. These plots were obtained from a specific model that belongs to the slow virus growth class, i.e. . Parameters were chosen as follows: (a) r = 1; β = 0.8; a = 0.5; ε1 = 20; ε2 = 10; η = 108; x0 = 100 and 10,000, respectively; y0 = 10. For (b) r = 1; β = 1; a = 0.5; ε1 = 10; ε2 = 11$; η = 108; x0 = 10; y0 = 1.