Cancer cell fate in response to drugs has been studied with both discrete and continuous models using knowledge driven approaches. For example, the study in [2] focused on discrete modelling of the apoptosis network, by constructing a model for cell fate with 25 key regulatory genes (e.g. Casp3, BCL2, XIAP, etc.). Cell survival pathways with cell death (necrosis and apoptosis) pathway were combined to model three cell fates, namely apoptosis, proliferation and survival. GINsim [3] software was used to perform simulation to assess the importance of Cytokines (e.g. TNF, FASL) in deciding the cell fate. In another study, Hong et al. [4] analysed the continuous model of apoptosis triggered by the drug Cisplatin. They initially constructed apoptosis pathways using existing literature. This model was configured to respond to the external stimulus, i.e. the drug Cisplatin. To analyse the functions of various signalling pathways and their crosstalk, Hong et al. integrated three apoptosis pathways, namely death receptors (e.g. FasL) induced pathway, mitochondrial pathway and ER stress pathway. Using their differential equation based model they found that the apoptosis caused by Cisplatin was dependent on doses and time. The level of apoptosis was almost stagnant at higher concentration of drug. They also observed that mitochondrial pathway has strongest effect on apoptosis (among the three pathways) [4].