A hybrid cellular automaton model of bioreductive drug transportation with protein binding

Drug binding to its surrounding proteins is known as a resistive factor towards effective drug penetration that reduces the diffusing drug concentration inside the tumour. This drug reduction fails to remove tumour mass completely and becomes one cause of treatment failure and tumour recurrence. Various mathematical models have been developed to calculate bioreductive drug (particularly, tirapazamine) characteristics by assessing in-vitro and in-vivo experimental results. So far, no attempt has been reported that practices a computerized model to discover tirapazamine (TPZ) transport under the influence of protein binding inside the solid tumour and at cellular level. This paper presents an investigation into the development of an in-silico model that mimics the behavior of heterogeneous tumour mass towards its treatment with TPZ. An artificial Neural Network model is proposed demonstrate the dynamics of tumour growth model. The model is implemented through a set of experiments based on clinical and reported data. The model is used to monitor the influence of surrounding proteins on TPZ cytotoxicity, concentrations and metabolism at cellular level and demonstrated these impacts on tumour morphology and hypoxic cells survival fractions. The results showed no/less cytotoxicity for cells located at the most distal locations from the source (blood vessel) of drug supply. These results suggested that the impaired drug transport is the main cause of solid cancer treatment failure.