Centre for Translational Epidemiology (TrEpi)
Centre for Translational Epidemiology (TrEpi)

Research goals

Data from health registries and life sciences will be combined and given new use to identify causal mechanisms, prevention options, therapeutic targets, and eventually new treatment principles.

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Big data and artificial intelligence are important to develop novel translational framework.

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The primary and secondary research goals of TrEpi are to: 

1. Establish a translational framework integrating multiple approaches to causality by

  • assembling and accommodating unique large-scale registry and biomedical data
  • merging and advancing new methods and approaches from epidemiology, medical statistics, biomedicine, and bioinformatics
  • developing novel forward and reverse translational pipelines, verifying causal inferences from registry data in experimental model systems, and vice versa

2. Analyse these data to integrate disease entities by

  • applying the translational pipelines to identify causal mechanisms shared by CNS NCDs 
  • creating personalised and precise risk predictions
  •  identifying new targets of intervention and translate these targets into novel options for primary prevention and treatment

3. Apply the translational pipelines to other NCDs to test their broader utility

4. Build an interdisciplinary research environment to train a new generation of scientists in translational epidemiology


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