"The incidence of paediatric onset Inflammatory Bowel Diseases (PIBD) has risen dramatically in recent decades. Compared to adult forms, PIBD reflects a more severe disease, more often requiring aggressive treatment with immunomodulators, and thereby exposing children to a life-long risk of serious disease and treatment-related adverse events, such as infections and malignancies. Therefore, there is an urgent need to develop strategies which balance, on an individual basis, therapeutic effectiveness with risks of treatment.<br/>The overall goal of this proposal is to develop and validate a treatment algorithm for PIBD based on high or low risk predictors for early complicated or relapsing disease. This will improve effectiveness, while reducing treatment related risks and life-long complications due to uncontrolled disease progression.<br/><br/>To attain this goal 3 specific aims are proposed under the umbrella of an international network, the ""PIBD-net"": <br/>1) Development of an accessible and feasible risk-stratified treatment algorithm for new onset paediatric IBD on an existing inception cohort and validation in an independent cohort<br/>2) Generation of a prospective large longterm real world inception cohort in a registry designed to analyze effectiveness and safety signals and correlate them to individual risk factors <br/>3) Design and performance of a risk algorithm-based prospective large-scale multicenter randomized clinical trial (RCT) (stratification into high or low risk groups based on specific aim#1) in order to provide optimal personalized therapy : low risk azathioprine vx. methotrexate, high risk : methotrexate vx. adalimumab<br/>This project will translate into the first risk-stratified PIBD treatment algorithms allowing optimization of medical therapy while minimizing treatment-related risk (personalized medicine).<br/><br/>"