Initial Project Plan

CTMM-TraIT's original project plan - updated 07-03-2018


One of the main goals of the Center for Translational Molecular Medicine (CTMM) was to develop well-validated biomarkers for some of the world’s most prevalent diseases. This work was performed in 21 public-private partnerships which are aligned in large, multi-disciplinary and multi-institutional consortia.

Much of the research conducted in CTMM centered around preventive and personalized medicine. Early detection of disease in asymptomatic individuals, the use of molecular markers and imaging for prognosis of disease outcomes, and the prediction and improvement of therapy efficacy were all major objectives of the CTMM research program.


Ever-expanding data

All CTMM projects adopted the same basic approach, namely to correlate variations in disease phenotype to variations in underlying biology in order to produce personalized solutions that improve patient outcomes. Their challenge was to translate these ‘personalized healthcare’ solutions to the clinic. Typical questions that addressed included: "Which out of tens of thousands of biomarkers can predict a good or bad outcome?"     "Which out of tens of thousands of biomarkers can predict whether or not a patient will benefit from a particular therapy?"

The phenomenal size of the datasets produced in the CTMM research projects and their distribution over different research laboratories and clinics required an informatics infrastructure that allowed the seamless integration and exchange of large amounts of newly-generated and legacy data as well as complex data analysis. Securing access to properly preserved data for use by future generations of researchers was also an important aspect that needed to be addressed. At the moment, scientists are faced with myriad resources (databases, websites, tools, algorithms), each covering a small section of their research space and using many different standards.

The result is that experimentalists who are not computational experts find it difficult to fully interact with and use all the relevant data.



The CTMM-TraIT (Translational Research IT) project addressed the problem by organizing, deploying and managing an IT infrastructure for data and workflow management, initially targeting the needs of CTMM projects but at a later stage also addressing the needs of the broader community of translational researchers in The Netherlands.

TraIT enables seamless integration and querying of information across the four major domains of translational research - clinical, imaging, biobanking and experimental (any-omics).

It specifically aimed to:
- provide a sustainable and scalable translational research information infrastructure that allows industry and public organizations to share data, analyses and understanding, driven by community-endorsed open data and technical standards;
- provide powerful, accessible, high-quality tools that allow scientists to interact and explore a unified translational medicine space - i.e. the TraIT tools should be interoperable with other systems, but, above all, also be intra-operable between the individual TraIT work packages; 
- provide powerful accessible, high-quality tools that allow translational researchers to manage the business processes of translational research; 
- build as much as possible on existing solutions (e.g. caBIG, PSI) and only develop new solutions for unmet needs; 
- maintain a user-oriented process-driven approach throughout.

The TraIT project’s initial budget of between € 16-20 million was financed according to standard CTMM policies - 50% from government funding, 25% from the TraIT project’s private partners and 25% from it's academic partners.