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Implementing clinical trial data sharing requires training a new generation of biomedical researchers

Nature Medicine volume 29, pages 298–301 (2023)Cite this article

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Data sharing enhances the value of medical research and builds trust in clinical trials, but more biomedical researchers need to be trained in these approaches, which include meta-research, data science and ethical, legal and social issues.

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Fig. 1: Elements of data sharing.

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Author information

Authors and Affiliations

  1. Ludwig-Maximilians University Munich, Institute for Medical Information Processing, Biometry, and Epidemiology, Munich, Germany

    Ulrich Mansmann

  2. Université Rennes, CHU Rennes, Inserm, Centre d’Investigation Clinique de Rennes (CIC1414), Service de Pharmacologie Clinique, Institut de Recherche en Santé, Environnement et Travail (Irset), UMR S 1085, EHESP, Rennes, France

    Clara Locher & Florian Naudet

  3. Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany

    Fabian Prasser & Tracey Weissgerber

  4. Department of Medical Informatics, University Medical Center, Göttingen, Germany

    Ulrich Sax

  5. Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria

    Martin Posch

  6. Hospices Civils de Lyon, Pôle Santé Publique, Unité de Recherche Clinique, Lyon, France

    Evelyne Decullier

  7. Department of General Psychology, University of Padova, Padova, Italy

    Ioana A. Cristea

  8. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands

    Thomas P. A. Debray

  9. Smart Data Analysis and Statistics B.V., Utrecht, The Netherlands

    Thomas P. A. Debray

  10. Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland

    Leonhard Held

  11. Center for Journalology, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada

    David Moher

  12. School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada

    David Moher

  13. Department of Medicine, Stanford University, Stanford, CA, USA

    John P. A. Ioannidis

  14. Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA

    John P. A. Ioannidis

  15. Department of Biomedical Data Science, Stanford University, Stanford, CA, USA

    John P. A. Ioannidis

  16. Department of Statistics, Stanford University, Stanford, CA, USA

    John P. A. Ioannidis

  17. Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA

    John P. A. Ioannidis

  18. Section of General Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA

    Joseph S. Ross

  19. Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA

    Joseph S. Ross

  20. Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, CT, USA

    Joseph S. Ross

  21. European Clinical Research Infrastructure Network (ECRIN), Düsseldorf, Germany

    Christian Ohmann

  22. Institut Universitaire de France (IUF), Paris, France

    Florian Naudet

Authors
  1. Ulrich Mansmann
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  2. Clara Locher
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  3. Fabian Prasser
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  4. Tracey Weissgerber
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  5. Ulrich Sax
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  6. Martin Posch
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  9. Thomas P. A. Debray
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  10. Leonhard Held
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  11. David Moher
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  12. John P. A. Ioannidis
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  13. Joseph S. Ross
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  14. Christian Ohmann
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  15. Florian Naudet
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Corresponding author

Correspondence to Ulrich Mansmann.

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Competing interests

T.D. owns a company that provides consulting services to life science industries, although no support was received when contributing to this paper. D.M. receives funding from the Digital Research Alliance of Canada to develop a Data Champions program in Medicine. J.S.R., receives research support through Yale University from Johnson and Johnson to develop methods of clinical trial data sharing. All other authors declare no competing interests.

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Mansmann, U., Locher, C., Prasser, F. et al. Implementing clinical trial data sharing requires training a new generation of biomedical researchers. Nat Med 29, 298–301 (2023). https://doi.org/10.1038/s41591-022-02080-y

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