Vascular Biogenics Ltd (VBLT)

[gr8db8]

While we wait for the results, this deck is worth revisiting. From slides 48-53 (download presentation at bottom of page):
https://sigport.org/documents/pca-based-algorithm-longitudinal-brain-tumor-stage-classification-and-dynamicalmodeling

Figures illustrates how the therapeutic Fas-c protein successfully controls the trajectory of Tumor Cells to an equilibrium state that approaches zero (y=0.77). Treatment proved also successful in controlling TNF-a which approaches zero (x=0.0018). These results agree with the findings in actual biological experiments between Tumor cells, Effector cells and TNF-a. With virotherapy treatment, the system moved from a pathological state (Tumor cells ?0) to a normal state where Tumor cells, effector cells and TNF-a are approaching zero

Figure 32 compares cells dynamics between two cases: with and without VB-111 treatment and for different antigenic tumors. It is apparent that our model captured the therapeutic properties of Fas-c on tumor cells, effector cells and TNF-a. In the case gene therapy is not administered , regardless of the level of tumor antigenicity , the cell dynamics exhibit oscillatory behavior alternating between different states (fig c,d). When VB-111 gene therapy is administered, however, the previously perturbed states are stabilized with a Fas-c protein killing rate of ß=10 (fig a,b).

-it is apparent that our model successfully captures the decay and stabilization of tumor cells by VB-111 monotherapy