In particular, highly non linear input output relationships are usually displayed in cell signalling networks, with a number of emergent properties, such as adaptive responses and robust switching inhibitor Gefitinib by positive feedback. It is worth emphasizing that the dynamic interactions and signal transmission in these chemical networks control cellular decision making and cellular responses such as movement, apoptosis etc. Considerable effort has been devoted to developing mathematical models to predict drug concentration and drug effect on solid tumours. Com partmental models have been widely adopted for prediction of temporal profiles of drug concentration in designed compartments, particularly drug concentration in blood in pharmacokinetic studies.

To obtain spatio temporal drug distributions in a given tumour geometry, it is ne cessary to explicitly account for drug transport. After drug concentrations are obtained, suitable pharmacodynamic models can be used to predict the effect of drug as a function of drug concen tration and/or as a function of time following drug admin istration in a phenomenological and empirical manner, with elaboration of observed data thus neglecting detailed underlying mechanisms. On the other hand, de terministic models can be used to describe the tumour response by assuming a drug concentration dependent tumour growth characteristic or tumour death kinetics. Unfortunately, mathematical models addressing the above mentioned areas have been developed separately. furthermore, they often bypass a key component that is the dynamic process of cellular signal transduction.

While all these models are capable of providing certain levels of insights, none of them offers a transparent and integrated description of drug transport and drug effect accounting for the associated cellular signalling. In this study, an integrated systems based mathematical modelling framework is employed and extended, which captures the information flow from drug delivery to the outcome, thus including biological transport processes of drugs and cellular response and accounting for dynamics of the relevant signal transduction. This allows us to begin to probe and elucidate different aspects of the roles and the interaction of transport and intracellular signalling dynamics. In a spatially distributed Entinostat system, intracellular signalling is triggered in response to heterogeneous drug stimuli delivered through transport pathways.

It must be emphasized selleckbio here that drug stimuli are dynamic, while drug transport can be affected by many tissue level features and intracellular dynamics is highly nonlinear. Finally the dynamic coupling of these factors is not necessarily uni directional. For instance the tissue scale properties and features could be a potential factor in affecting drug trans port. as an example, it is found that apoptosis inducing pretreatment enhances drug delivery.