The MAP-kinase pathway is a major pathway in relaying signals from the plasma membrane into the nucleus. Its comprehensive understanding is needed for rational anti-cancer therapies.

SIMAP will develop a comprehensive and robust simulation model of the pathway; populating it with kinetic parameters extracted from the literature and experimental work; simulating various types of inputs into the model; creating qualitative predictions and verifying them with independent experimentations. The model will integrate and analyse data from various types of resources vertically ranging from single molecule information, pathway modelling, up to clinical data and patient's response. SIMAP pioneers the integration of clinical phenotype into this improved biochemical model. Such multi-scale modelling has never been done in the field of Systems Biology and is a step forward.

Combining generic mechanistic modelling of the biochemical behaviour, accompanied by new generic mining techniques and clinical data integration, will create a multidisciplinary platform prototype suitable for modelling of other cancer related pathways.

Our approach will enable hypothesis-driven research aimed at the establishment of system level computational platforms available for various pharmaceutical applications. The concepts and methods we will develop will lead to the design of new therapeutic drugs, decrease the attrition rate of new drugs and make it possible to select patients on the basis of individual parameters of disease. Modelling-driven predictions regarding the impact of drug combinations will permit us to dramatically improve the design of pre-clinical and clinical trials, enhance patient response and limit adverse effects. Eventually this will optimise Public Health resources leading to significant pharmacoeconomic benefit.

The project is lead by a drug and diagnostic discovery SME and an interdisciplinary industrial and academic leading teams of investigators.