Activities

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O1: Identify relevant clinical and pre-clinical parameters for predicting treatment outcomes

WP 1.1 Identify clinical predictors of treatment outcome, adverse effects and risk of infection for CLL patients from phase II and III trials

WP 1.2 Define functional biomarkers as predictors of treatment response for patient stratification and prediction of therapeutic outcomes

WP 1.3 Identify genomic biomarkers for treatment sensitivity and resistance

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O2: Develop statistical models and ICT platforms for predicting optimal treatment regimens

WP 2.1 Establish a common data storage and sharing platform providing secured cloud-based access for each partner

WP 2.2 Machine learning for identifying multi-omics biomarker panels for treatment responses of individual CLL patients

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O3: Cost-effective implementation of the system in future clinical trials and clinical practice

WP3.1 Economic analysis of the personalized medicine decision support system, taking into account patient outcomes, quality of life and socio-economic context

WP3.2 Clinical implementation of the PM solution in a prospective clinical trial in Norway

WP3.3 Patient-centric implementation of the decision support system to different healthcare systems

WP3.4 Dissemination and communication between project participants and end users

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This work is supported by a grant of:

The Research Council of Norway (RCN)	Academy of Finland, (AKA)	German Federal Ministry of Education and Research (BMBF)	Innovation Fond Denmark, IFD	Romanian National Authority for Scientific Research and Innovation, CCDI – UEFISCDI, project number ERANET-PERMED-CLL-CLUE 196, within PNCDI III

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