Events
Following network events are planned during the course of the project.
Schloss Fürstenried, Munich, September 9. - 13. 2024
Kick-off propaedeutic training
Schloss Reisensburg, Günzburg, January 27. - 31. 2025
Schooling (S1)
Rechenzentrum Göttingen, July 7. - 11. 2025
Datathon (D1)
Kick-off propaedeutic training
The Propaedeutic Training introduces the key principles to request and access patient level data: Concepts of trial protocols and the legal/regulatory aspects of CTDS. ESRs will learn the management of complex data-sets by using meta-data (FAIR principles). An introduction to reproducibility issues and biostatistical principles for clinical trials is provided as well as to reporting guidelines and how Meta-Research is performed on clinical trials results. This event will introduce all beneficiaries and partners to the group of ESRs and put them on the same starting positions. It will be used to calibrate expectations on both sides and design individual career development plans (CDPs).
Schooling events
The topic of the first school (S1) is Data management and analytical skills for sharer/re-users. Teaching will extend basic knowledge on clinical trial design, trial protocols (and their submission to an ethics committee), standards for clinical trials data (e.g. CDISC, relationship to FAIR, OMOP for non-randomised studies) and analysis (developing a statistical analysis plan), good practice in statistical computing (reproducible workflows), standards of data protection in CTDS (demonstrated by an anonymisation game), legal frameworks for DS (entering a DS agreement, tailored sharing approaches, e.g. federated network, or sharing of specific aggregate data following an SAP), techniques to prepare a data-set for DS, adopting an Open Science workflow. The second school (S2) is on Best practices in DS and Meta-Research. Teaching will cover: Innovative strategies for data protection and their relevance for CTDS (methods of privacy preserving analyses and federated computing); overview of the different patient level data access models; IPD related topics as basic principles of meta-analysis, methods for combining IPD from multiple trials (and possibly non-randomised studies), methods for comparing multiple interventions, and methods for addressing data quality issues (missing data, measurement error, confounding); advanced use of Open Science workflows, and tools and their application in Meta-Research. The ELSI training introduce the topics: CTDS from a legal, societal, and philosophical point of view as well as state of the art how to do research on patients’ perception of CTDS. The third school (S3) is on the Impact of CTDS and covers the topics: Instruments to incentivise CTDS, instruments to measure the impact of CTDS, advanced issues in Meta-Research on the impact of CTDS. How to measure the impact of data sharing from the perspective of different stakeholders? What are the challenges for the industry / academia to perform CTDS?
Datathons
Datathons need time to be prepared, to do active work on the data, to discuss the results within and between teams, and to write a manuscript. Parts 2 and 3 will be in presence. Each datathon will be started during the schooling event before. Teams will learn about the topic and implementation details. SHARE-CTD members will build 5 teams. During the three months after the schooling event, the ESRs and their supervisors (accompanied by volunteer clinicians from our medical centres) will develop and register a protocol (or project proposal). Protocols will be reviewed by different stakeholders (e.g. input from patients on relevant outcomes, input from statisticians on the analysis plan, input from clinicians on research question, etc.). ESRs will have to handle ethical, privacy protection, and intellectual property issues. They will have to formulate hypotheses based on a state-of-the-art literature search, develop an analytic plan, and decide how to present the results. They have to handle a complex data-set by using the FAIR principles. Each team will implement an appropriate Open Science pipeline to perform their analyses (E.g. registration of the statistical analysis plan, sharing of code etc.). Data will be provided by our partner YODA within a secure DS environment . Conduct of these projects and transparent reporting of the corresponding results will use guidelines such as PRISMA-IPD or TRIPOD-Cluster. The different teams will work according to the Many Analyst Project format to explore whether there are converging or divergent views. Many Analysts’ projects focus on the diversity of views for a data-analytic task and systematically assess whether results and conclusions are dependent on the chosen analytical strategy. These projects elucidate the need for formal reproducible workflows and specific scientific strategies to address divergent views. In the first datathon (D1), participants will re-analyse a clinical trial. As an output, the group will draft a collaborative research paper about inferential reproducibility of this specific clinical trial. In the second datathon (D2), each team of researchers will design and perform an IPD meta-analysis. As an output, the group will draft a collaborative research paper about inferential reproducibility of this specific IPD meta-analysis. The third datathon (D3) focuses on a secondary analysis of clinical trial data and follows the example of the SPRINT challenge : The importance of the work will be assessed by a jury of patients and the scientific quality of the work will be assessed by the members of the network. Patients, domain experts and clinicians will be involved both as external advisors to provide feedback, and as part of a jury that will assess the potential impact of each research question. As an output, the group will draft a collaborative research paper about secondary analyses of clinical trial data.
Professional training
Professional training will be organised in three two-day sessions. The first professional training (PT1) will involve community building elements with focus on developing skills for: (1) How to interact into a multicultural setting, (2) team building, (3) success skills, (4) moderation skills, (5) presenting scientific research in social media. The second professional training (PT2) will concentrate on employment issues for our ESRs from the perspective of the different stakeholders involved in the project. It will also introduce negotiating issues and offer advice regarding communication between data holders and researchers. PT2 will address a variety of stakeholders, including the pharmaceutical industry, academia and regulatory authorities. The third professional training (PT3) will assess the scientific results of the ESRs from different viewpoints using the impact criteria discussed in the third schooling event, which focus on the values of the network (openness, DS and societal impact). This session will include a specific workshop organised by PhD students, focused on what ESRs have learned, where the group succeeded vs. failed in CTDS, and how the scientific community can do CTDS better.
Conference
We will close our project with a conference summarising and presenting our results and experiences to the different stakeholders and expecting their feedback.
