“The European cancer informatics landscape: Challenges for the biomedical informatics community”

It is becoming increasingly clear that a comprehensive analysis of biological systems requires the integration of all fingerprints of cellular function: genome sequence, maps of gene expression, protein expression, metabolic output, and in vivo enzymatic expression (activity). As stated ldquoAlthough the industry once suffered from a lack of qualified targets and candidate drugs, lead scientists must now decide where to start amidst the overload of biological data. In our opinion, this phenomenon has shifted the bottleneck in drug discovery from data collection to data integration, analysis and interpretation.rdquo This need for integration is to some extent clear in the case of complex, multifactorial diseases, such as obesity, diabetes, hypertension, schizophrenia (and other diseases of the nervous system, including Parkinsonpsilas and Alzheimerpsilas) and cancer. Cancer is a highly complex and heterogeneous disease which involves a succession of genetic changes that eventually results in the conversion of normal cells into cancerous ones. It is obvious that a complete knowledge of these processes requires the integration and analysis of massive amounts of data as is being collected from current genomic, proteomic and metabolic platforms in the context of exploratory research and formally designed clinical studies. Robust data management and analysis systems are becoming essential enablers of these studies. Predicted benefits include an enhanced ability to conduct meta-analyses, an increase in the usable lifespan of data, a reduction in the total cost of IT infrastructure, and an increased opportunity for the development of third party software tools. This presentation will critically examine European and global efforts towards developing publicly-accessible interoperable and distributed production systems in the health and life sciences (with a focus on cancer), via ontologies, formal metadata, service oriented architectures, and grid computing models. Significan- - t engineering challenges need to be successfully addressed if we are going to realize our vision of therapies specifically designed to treat each individualpsilas cancer in highly targeted ways. A range of such engineering challenges will be identified and discussed.