INTRODUCTION DEFINITIONS DATABASE ANALYSES ADVANCED MODELING MANAGEMENT CLIENT LIST PUBLICATIONS PRESS   Data Mining International SA is a swiss based independant research agency, member of the BioAlps european hub of bio-sciences, specialized in advanced mathematical modeling and computarized techniques with the objective to generate relevant information from various kind of databases and scientific information. Data Mining International has developed a unique experience in international project management and scientific expertise. Data Mining International has initiated and is managing the European Consortium in Healthcare Outcomes and Cost-Benefit research ECHOUTCOME , which is a new European project in the frame of the Seventh Framework Programme of the European commission. For the first time, this innovative project will compare the health system organizations of the 27 member states and will study the robustness of health outcomes currently used by health technology assessment authorities in Europe. The scientific validity of synthetic indicators such as the Quality Adjusted Life Years (QALY), the Disability Adjusted Life Years (DALY) or Healthy Years Equivalent (HYE) will be extensively investigated and recommendations will be proposed to member states at the end of the project in 2013. In addition of Data Mining International which manage the project, the ECHOUTCOME consortium is composed by experts from the University of Bocconi (Italy), the Université Libre de Bruxelles (Belgium),the French Society of Health Economics (France), The Cyklad Group (France), Lyon Ingénierie Projets (France) and the Claude Bernard University (France), which coordinate the project. Area of expertise of Data Mining International are : Advanced Modeling Advanced Statistical Analyses Multicriteria ranking Small Sample Significant Simulations Advanced Data Mining and Text Mining           Advanced Statistical Analyses   Advanced statistical analyses are particularly relevant in early development in Life science (Biotech, Biopharma, Medtech, etc.) such as proof concept studies, phase I to IV clinical studies. Such analyses are becoming very useful in clinical studies with non conclusive results. Of course, advanced statistical analyses can be applied to any areas such as finance, market research or operational research. Multi-criteria analyses Pharmacoeconomic advanced analyses Quality of life instrument development and validation Quality of life advanced analyses Health indicators validation Satisfaction/preferences development instrument Satisfaction/preferences advanced analyses Responders /not responders segmentation High risk of adverse events / low risk of adverse events segmentation Missed data management Non significant results Poor recruitment Extreme values management Time series analysis Modelling over time Modelling of new therapeutic regimens Relations between qualitative and quantitative variables Expertise in new clinical study protocols Databases can be related to : Market research Pricing & Reimbursement Pharmacoeconomic studies Epidemiological studies Profiling Registries / Observatories transportation safety and optimization studies Weather & Environmental studies           Advanced Modeling   Advanced Modeling Clinical and Health Technology assessment modeling Advanced forecasting Simulation Modeling Optimization Modeling           Small samples significance simulations   Rare diseases Pharmacogenetics / Pharmacogenomics Experimental medicine Phase 1 & Phase 2 Medical devices           Advanced Data Mining   Large data collections are now very frequent in business world are more and more complexes. They are included in heterogeneous databases and located in various locations. The objectives of data treatment and analysis are : Knowledge extraction Decision making in using techniques coming from various scientific areas such as statistics, mathematics and computerized science, coordinated in an integrated approach in order to extract information.     This integrated approach is named Data Mining , which is now considered as a specific science based on factorial analysis, sampling techniques, statistical techniques, computerized techniques in databases management, extraction techniques knowledge representation (Bayesian networks, neural networks), information technology “distributed” or various simulation techniques.

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