Biological processes are driven by complex networks of interactions between molecular and cellular components. Predicting the outcome of potential disturbances is of prime importance to be able to prevent disease, as well as to identify possible therapies for diseases, which are already present. To predict the behaviour of such complex networks, we will have to develop general models of the processes involved, based on information on pathways derived from genetic and molecular approaches, to ‘individualise’ these by applying ‘genomics’ scale analysis techniques (e.g. genome and/or transcriptome analysis by next-gen sequencing techniques-genomics), and to explore the behaviour of these models computationally (systems biology). We are using a combination of high throughput sequencing of genome and transcriptome of both tumor and patient to establish predictive models (virtual patients), which ultimately will reflect the response of real patients to specific therapies in oncology and other areas of medicine.