gms | German Medical Science

Introduction: As a part of Netzwerk Universitätsmedizin (NUM), the project NUKLEUS (NUM Klinische Epidemiologie- und Studienplattform) [1] offers like the German Centre for Cardiovascular Research (DZHK) [2] the necessary infrastructure for quick realization in planning and evaluation of clinical studies, including the use of secondary data. We present the challenges of the NUKLEUS transfer office (TO) as a central part of the data transfer process in cooperation with eight project partners.

Methods: To guarantee a smooth data transfer process each research proposal needs to go through a series of necessary steps. After approval through the use and access (UAC) process, the proposal gets reviewed by members of the TO to determine unclear parts and missing information. Subsequently, an appointment for an online kick-off meeting with the research team is organized to clarify questions from both sides. The meeting is critical, as besides clarifying questions, the project partners can also hear directly the scientific intent of the proposal. Subsequently, the patient collective can be calculated based on the agreed criteria in terms of clinical data, imaging data, and biological samples in a feasibility calculation. The TO gathers all needed information through interfaces from the different teams, for example, information about available biological samples. If a feasibility calculation does not reach the minimal patient count or more questions emerge, another online meeting with the proposal’s team will be scheduled. This may result in an alteration of the criteria. Even after the initial data transfer, research teams often have follow-up requests leading to multiple transfers for each proposal.

Results: Currently the NUKLEUS transfer office has processed 111 research proposals with 180 separate data transfers. 26 proposals had biological samples, and 15 had imaging data included.

Lessons learned: The process of determining a fitting patient collective for each research proposal is a highly individual and challenging process. Proper consulting with both research teams and NUKLEUS partners is critical. Therefore, it is challenging to automate, and likely first planned attempts like the inclusion of the Feasibility Explorer [3], [4] would only cover parts of the requirements. Automating steps is key in order to be able to efficiently process larger numbers of proposals covering different data cohorts. For example, we use an internal R package to cover recurring steps and calculations. The process is still costly in time and needed personnel and the inclusion of additional data cohorts would demand further automation. Also, a significant part of the proposals want to include the German Corona Consensus Dataset (GECCO) and the alignment of the National Pandemic Cohort Network (NAPKON) elements to it is still not fully realized [5] and special cases for each data cohort would need to be addressed.

Funding: German Federal Ministry of Education and Research

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.