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 consequent analysis will integrate 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 together with this improved biochemical model. Such multi-scale modelling is groundbreaking in the field of Systems Biology.
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 can 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 may permit us to dramatically improve the design of pre-clinical and clinical trials, enhance patient response and limit adverse effects. Eventually, this may optimize Public Health resources and lead to significant pharmacoeconomic benefit.
The project is lead by a drug and diagnostic discovery SME and interdisciplinary industrial and academic leading teams of investigators.

• Incorporate low-level biochemical modelling of individual molecules (WP3, WP4, WP5)
• Simulate the kinetic behaviour of the pathway (WP3)
• Add genomic and proteomic data to the model (WP7) 
• Incorporate individual patients�f responses (WP6, WP7) 
• Analyze sub-population of responses (WP7, WP8)

The SIMAP project is tackling a key cause to many forms of cancer and as such a major societal and economic challenge. The results from the project will be available through a utility prototype that will be a prototype of how to use current EGFR-MAP kinase model, and similar models that can be built on similar technologies, for clinical research. In the long run it is hoped the prototype will serve as a tool to improve the bedside treatment of patients based on a multi-level genomic/proteomic profile.