Translational Research IT (TraIT)

Implementing and sustaining a long-lasting IT infrastructure for translational research

Translational research programs depend increasingly on a diverse collection of complex datasets that are often phenomenal in size. To ensure maximum benefit, integrated tools for data collection, analysis and management are required, as well as an infrastructure that supports collaboration between research centers. The Translational Research IT (TraIT) project was launched in October 2011 to address these informatics challenges.

icon_Money €19 M

funding from FES, VWS & partners

icon_trendline >4,000

users as of March 2017

About TraIT

The Translational Research IT (TraIT) project provides an easy-to-access and easy-to-use infrastructure for data sharing, together with a set of tools for further exploration of the collected data. It operates across the four major domains of translational research: clinical, imaging, biobanking, and experimental (any-omics). TraIT gives scientists within multi-site projects the resources needed to share and disseminate data and analyses. Importantly, the project aimed to adopt and adapt existing and proven solutions (e.g. XNAT, Ldot, cBioPortal) rather than embarking on major software development projects. As of January 2020, more than 4000 researchers from over 400 studies and dispersed over more than 500 locations are making use of one or more of TraIT’s services. Visit the TraIT website for more information about the project.

Realizing sustainable infrastructure for biomedical research

Since its inception, TraIT has grown from 11 to 32 participating organizations, including all Dutch university medical centers, charities, and a variety of private partners. CTMM initiated the project in close collaboration with members of the research community, identifying opportunities for partnerships and developing an efficient and well-defined management structure. From January 2016, CTMM’s roles and responsibilities within TraIT are provided under the Lygature brand, while the core TraIT facilities are integrated into Health-RI as of January 2020:

  • Governance.  Lygature is the legal entity coordinating TraIT. It takes responsibility for sustainability and legal discussions around the setup of a long lasting infrastructure for the Dutch and international biomedical community. In addition, Lygature provides financial management.
  • Innovation activities. To ensure sustainability, Lygature collaborates with consortium partners to attract new funding for maintenance and extension of the TraIT infrastructure in the context of Health-RI. Lygature is pivotal in creating strategic alliances with other infrastructure organizations (national and international), research funders, and patient representatives, so that further development can take place.
  • Operations. Lygature heads the operations team, which works on professional deployment of infrastructure, and of quality and service management. The team also handles end-user support and education, as well as branding and communications.

TraIT is an important example of Lygature’s mission to bring academia, industry, and society together in research infrastructure projects that allow participants to benefit from shared resources and data. It has required extensive expertise in data infrastructure, management, and science, and has helped to build many long-term partnerships. Lygature, together with the TraIT partners, continues to foster these partnerships.

Lygature together with

Project updates

  • TraIT OpenClinica Data Importer v2.0 released

    In order to automate and facilitate data capture in OpenClinica as much as possible TraIT has recently developed a completely new OpenClinica Data Importer (OCDI v2.0). Read more

  • TraIT welcomes its 3000th user

    The Translational Research IT (TraIT) project is happy to welcome its 3000th user.

    Alberto Traverso, researcher at Maastricht University and MAASTRO Clinic, recently applied to use the TraIT infrastructure for his study on lung cancer imaging. Traverso will use the National Biomedical Imaging Archive, one of the TraIT tools, to establish a centralized repository for imaging data.

    The Medical Physics doctorate comes from Italy originally and moved to Maastricht in October, to work in the Knowledge Engineering group of Prof. André Dekker. His research focuses on management of clinical data and developing tools for clinicians to take decisions in relation to cancer therapy.  “In our group we work a lot on radiomics, which is quite a new field. It’s a way of analyzing medical imaging data, especially scans from patients in the hospital.


    Within the big “Radiomics” project, Traverso and his colleagues are developing tools to automatically analyze the imaging data. “Now doctors look at the image, and of course they can say something about the properties of the tumors, but there is a lot of information invisible for the human eye. Therefore, we are working on an automatic way of extracting this information and relate it to clinical applications”.  Next to that, the group is working on data management and the quality of data. “We are building a platform for radiomics, an infrastructure to automatically collect all data. This is an international effort, with hospitals around the world involved.”

    Using the National Biomedical Imaging Archive

    The idea of the study was to have a common tool where all partners of the project can submit and collect anonymized data. “In principle you have quite a lot of data, because every scan that is made in the hospital can potentially be used. But there are two problems. Firstly, the data are decentralized, so it is difficult to get access. Secondly, data are often very different because the protocol of storage is different. We need to define data in a universal way, making it readable for machines.” The solution is the National Biomedical Imaging Archive (NBIA), that is used as a central repository, one of the most fundamental parts of the study. “The nice part of the tool is that it includes a quality control before publishing this data. This way you create homogenous data that can be further used for research.”

    Multi-site, multi partners

    For Traverso, it is the first time working with data on such international scale. “I was used to working with local data. Therefore, there was never a need for a big central repository. My supervisor (André Dekker) already used the NBIA tool in several projects, so it was natural that we started working with it.” The radiomics project is a big project, with the aim to collect 3000 patients from 10 partners from different sites, in the US, Asia and Europe. “We started working with the tool in January. At this moment, we are training our partners to work with it. And every week there are new people wanting to take part and share their data.”

    Towards personalized treatment

    The project of Traverso and his colleagues will run for at least 4 years. The first goal is to build the radiomics platform. Eventually, retrieving more information about the properties of the tumors offers the opportunity to create a more personalized treatment. “You don’t want to give every patient the general treatment. As each tumor is different for each patient, you want to differentiate this, according to the properties of the tumor and taking into account what you see on the image.” Currently invasive biopsies are needed for diagnosis. “If you can read more from the images, we could use them as predictive tools for cancer therapy and find the treatment that works best for the specific tumor.”


    Eventually Traverso would like the data to be readable for machines, so they can be fully automatically analyzed. “When I go to conferences I notice that clinicians are wary of this automation. They fear computers will substitute their jobs. This is not the case; it is always based on human design. We can use computers to save time, so doctors can focus on their expertise. Computers can notice features that are invisible for the human eye. But we need doctors to interpret the data.”

    Different languages

    The research project combines the interests of Traverso in working with clinical data and imaging processing. His experience in Torino, especially working with prof. Piergiorgio Cerello, (Turin Section if INFN, made this possible. “I really need to thank Piergiorgio for all the effort put in growing me as young researcher”. “After I finished my PhD in Medical Physics in Torino I applied for this position at Maastro Clinics. I like the broadness of the project, working with different people with various backgrounds, from computer science to medical researchers. It’s challenging. We speak different languages, look at the problem from different viewpoints. That’s what research really is about. Learning from each other and build new common knowledge.”

    For more information on the "Radiomics" project, please visit the MAASTRO Knowledge Engineering pages.

  • Report on TraIT years 2011-2016

    We have captured for you all the important information about the CTMM-TraIT years 2011-2016 in the output report.

    Integrating biological data with clinical phenotype data is at the core of translational research. The level of penetration of professional-grade IT in the field of translational research is contrasting its importance and the level of sophistication of e.g. the omics methods used. The CTMM TraIT project, in terms of concept, community building, technology development & deployment, and political decision making has had major effects on improving this situation.

    At present, TraIT has delivered one or more mature services for each of the aforementioned data domains in the translational research workflow: clinical (OpenClinica), imaging (e.g. NBIA, XNAT), biobanking (MOLGENIS catalogue in close collaboration with BBMRI-NL), and experimental (e.g. Galaxy, Phenotype DB). Data integration across these translational domains is provided by the TraIT service for tranSMART, an open-source solution for hypothesis-free browsing across clinical and genomics data. The TraIT services are made available in an on-line digital research environment, very much like an “MS office suite” for translational research, and are supported by a fully operational TraIT service center handling approximately ten user calls per day. This additional layer of services on top of often well-established open source solutions has been key to the user uptake of TraIT.

    With these results, TraIT has become an internationally recognized best practice in FAIR (i.e. findable, accessible, interoperable and reusable) data stewardship. TraIT has become one of the key components of the current BBMRI-NL (i.e. the Dutch national biobanking infrastructure) program, and one of the initiators of the comprehensive Dutch national infrastructure for personalized medicine & health research, Health-RI. It is anticipated that TraIT will become an integral part of the Health-RI services in the coming years. The transition of TraIT into Health-RI is currently being developed with the support of many stakeholders, most notably the Dutch Cancer Foundation KWF.

    TraIT Output booklet (download PDF)