Alternative models for sharing confidential biomedical data (original) (raw)

Nature Biotechnology volume 36, pages 391–392 (2018)Cite this article

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To the Editor:

Although much discussion has been focused on the need for more data sharing in the biomedical community, less attention has been paid to new kinds of biomedical data sharing, particularly the sharing of confidential patient data. In the traditional paradigm of data sharing, researchers transfer their data directly to data modelers. Here we describe an alternative model that allows the protection of confidential data through a process we term 'model to data' (MTD). In the MTD model, the flow of information between data generators and data modelers is reversed. This new sharing paradigm has been successfully demonstrated in crowdsourced competitions and represents a promising alternative for increasing the use of data that cannot—or will not—be more broadly shared.

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Figure 1: Sharing paradigms for data challenges.

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Authors and Affiliations

  1. Sage Bionetworks, Seattle, Washington, USA
    Justin Guinney
  2. RWTH Aachen University, Faculty of Medicine, Germany
    Julio Saez-Rodriguez
  3. The European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
    Julio Saez-Rodriguez

Authors

  1. Justin Guinney
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  2. Julio Saez-Rodriguez
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Correspondence toJustin Guinney.

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The authors declare no competing financial interests.

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Guinney, J., Saez-Rodriguez, J. Alternative models for sharing confidential biomedical data.Nat Biotechnol 36, 391–392 (2018). https://doi.org/10.1038/nbt.4128

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