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Vision & Objectives

3TR aims to provide fundamental new insights into the mechanisms of response and non-response to treatment. Thereby, we challenge the conventional “single disease”-based approach, in which diseases are classified according to their end-organ involvement rather than the molecular pathways underpinning them.

Consequently, we propose a paradigm shift in the way we look at diseases: Promoting a scientific evidence-based rationale for treatment selection, rather than following the traditional trial and error approach, 3TR will have significant implications for future patient management and the assessment of efficacy, safety and quality of future health products.

On a more practical level, central work objectives are:

  • Establish a centralised data and sample management platform

    Establishment of centralised and standardised workflows, covering the full project life cycle, from sample collection and bio banking to clinical and molecular data production and storage enabling the swift profiling of the seven diseases in a de novo prospective collection. In doing so, a sustainable knowledge base and a unique sample resource for future work will be created .

  • Perform comprehensive molecular and clinical characterisation of a prospective patient cohort

    Comprehensive molecular and clinical characterisation of patient cohorts from seven different disorders that provide a solid data foundation for advanced bioinformatics, statistical and model-based analysis. A suite of state-of-the-art technologies will be applied providing data of increased granularity/resolution.

  • Deliver integrated analysis of all data using advanced bioinformatics/statistical and modelling methods

    Integrated analyses of existing and newly generated data using advanced bioinformatics/statistical pipelines and modelling methods to identify pathways of non-responsiveness, disease trajectories and clusters, commonalities and clinically relevant biomarkers. The project will develop inclusive models and algorithms for the integration of tissue, clinical, omics and microbiota data to be used as variables in the identification of classifiers and predictors of disease trajectories. This will be complemented by mechanistic models of the processes in the tissues reflecting the phenotype as well as an overall model of the immune system of every individual analysed.

  • Identify sets of predictive biomarkers of response/non-response to therapies

    Identification of sets of predictive biomarkers of response/non-response to therapies that can be introduced into a validation and qualification pipeline to prompt their path into clinical use for the benefit of patients.