Sharing and re-using clinical trial data to maximise impact (SHARE-CTD)

Clinical trial results are the source of foundational evidence for contemporary medical decision making. This evidence is widely used by regulatory bodies, health technology assessment agencies, and is considered the gold standard for assessing treatment effects. The value and trustworthiness of medical research may be enhanced by sharing of patient-level clinical trial data together with the code on which analyses are based as well as other materials such as the protocol, case report form, and data dictionary. Keeping this background in mind, clinical trial data sharing (CTDS) offers unique opportunities for external re-analysis, which enables conclusions to be re-examined, verified or, occasionally, corrected, thereby building trust. CTDS also allows individual participant data (IPD) meta-analysis and other strategies that build upon previous data and code, such as secondary analyses and methodological work. CTDS should accelerate discovery, reduce false discovery rates, and potentially discourage misconduct and research waste, as well as allowing more value to be drawn from the original research investment. CTDS honours the generosity of clinical trial participants, because it maximises the utility of the data they provide, and is widely viewed as a positive feature by stakeholders involved in clinical trials, including trial participants.

In this European PhD Curriculum, students will leverage diverse fields, including biostatistics, computer science, machine learning, and meta-research to establish robust practices and methodologies for clinical trial data sharing. They will work on a multi-disciplinary area, enhancing the utility of shared clinical trial data while safeguarding its integrity. Through their individual research efforts, they will contribute to expanding our understanding of data sharing and re-use, tackling issues from data anonymisation to outcome reporting bias. Furthermore, they will investigate the real-world impact of clinical trial data sharing on healthcare and medical practices. The overarching goal is to advance scientific knowledge in order to shape policy and guidelines, thereby revolutionising the way we share and use data in clinical trials.

Their research will be embedded and supported by a training programme based on theory, practice and experience. Doctoral candidates who complete the programme will know how to perform research to advance best practices for CTDS, and how to perform data sharing with a high level of professionalism. They will be able to address the following important issues: 1) enhancing public access to clinical study information, 2) reaffirming commitments to publish clinical trial results, 3) sharing results with patients who participate in clinical trials, 4) certifying procedures for sharing clinical trial information, and 5) enhancing data sharing with clinical researchers.

Through the involvement of a large international network of partners, SHARE-CTD will allow a profound interaction with a wide range of experts as well as problem-based interactive methods such as datathons that promote transparency, honesty and collaboration. It will prepare the candidates for a wide range of positions in academic and non-academic fields.

Projects provided by SHARE-CTD

1. Role of CTDS for validation of prognostic and predictive models for MS patients – Dr. Ulrich Mansmann, LMU München, Germany
2. Impact of clinical trial data sharing – Dr. Florian Naudet, University of Rennes, France
3. Innovative approaches to trial data anonymisation and its role for CTDS – Dr. Fabian Prasser, Charité, BIH, Germany
4. Automated screening tools for identifying data sharing, data-re-use and common reporting problems in clinical trials – Dr. Tracey Weissgerber, Charité, BIH, Germany
5. Methodology for FAIRification, Data Enrichment and Data Sharing – Dr. Ulrich Sax, University Medical Center Göttingen, Germany
6. Added value of meta-analyses of shared individual patient data (IPD) in mental health – Dr. Ioana-Alina Cristea, University of Padova, Italy
7. Towards Understanding and accepting data sharing within patients – Dr. Evelyne Decullier, Hospices Civils de Lyon, France
8. Methodology for cross-design synthesis – Dr. Valentijn de Jong, University Medical Center Utrecht, The Netherlands
9. Using shared historic data to augment prospective clinical trials – Dr. Martin Posch, Medical University Vienna, Austria
10. Evaluating outcome reporting bias in clinical trials – Dr. Leonhard Held, University of Zürich, Switzerland
11. Impact of clinical trial data sharing for pivotal trials in oncology – Dr. Clara Locher, University of Rennes, France.

The application process will follow the EU code of conduct (https://euraxess.ec.europa.eu/jobs/charter/code)