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. 2025 Apr 3;11(1):55.
doi: 10.1038/s41537-025-00560-x.

Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program

Tashrif Billah #  1 Kang Ik K Cho #  1 Owen Borders  2 Yoonho Chung  3   4 Michaela Ennis  5 Grace R Jacobs  1 Einat Liebenthal  3   4 Daniel H Mathalon  6   7 Dheshan Mohandass  2 Spero C Nicholas  6   7 Ofer Pasternak  1   2 Nora Penzel  2 Habiballah Rahimi Eichi  3   4 Phillip Wolff  8 Alan Anticevic  9   10 Kristen Laulette  11 Angela R Nunez  9   10 Zailyn Tamayo  9 Kate Buccilli  12   13 Beau-Luke Colton  12   13 Dominic B Dwyer  12   13 Larry Hendricks  12   13 Hok Pan Yuen  12   13 Jessica Spark  12   13 Sophie Tod  12   13 Holly Carrington  1 Justine T Chen  2 Michael J Coleman  1 Cheryl M Corcoran  14 Anastasia Haidar  1 Omar John  2 Sinead Kelly  1 Patricia J Marcy  15 Priya Matneja  15 Alessia McGowan  14 Susan E Ray  15 Simone Veale  1 Inge Winter-Van Rossum  14 Jean Addington  16 Kelly A Allott  12   13 Monica E Calkins  17 Scott R Clark  18   19 Ruben C Gur  17 Michael P Harms  20 Diana O Perkins  21 Kosha Ruparel  17 William S Stone  22 John Torous  22 Alison R Yung  23   24 Eirini Zoupou  17 Paolo Fusar-Poli  25   26 Vijay A Mittal  27 Jai L Shah  28   29 Daniel H Wolf  17 Guillermo Cecchi  30 Tina Kapur  1 Marek Kubicki  1   2 Kathryn Eve Lewandowski  4   31 Carrie E Bearden  11 Patrick D McGorry  12   13 René S Kahn  14 John M Kane  32   33 Barnaby Nelson  12   13 Scott W Woods  9   10 Martha E Shenton  1   2   34 Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ)Justin T Baker  3   4 Sylvain Bouix  35   36
Affiliations

Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program

Tashrif Billah et al. Schizophrenia (Heidelb). .

Abstract

Modern research management, particularly for publicly funded studies, assumes a data governance model in which grantees are considered stewards rather than owners of important data sets. Thus, there is an expectation that collected data are shared as widely as possible with the general research community. This presents problems in complex studies that involve sensitive health information. The latter requires balancing participant privacy with the needs of the research community. Here, we report on the data operation ecosystem crafted for the Accelerating Medicines Partnership® Schizophrenia project, an international observational study of young individuals at clinical high risk for developing a psychotic disorder. We review data capture systems, data dictionaries, organization principles, data flow, security, quality control protocols, data visualization, monitoring, and dissemination through the NIMH Data Archive platform. We focus on the interconnectedness of these steps, where our goal is to design a seamless data flow and an alignment with the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles while balancing local regulatory and ethical considerations. This process-oriented approach leverages automated pipelines for data flow to enhance data quality, speed, and collaboration, underscoring the project's contribution to advancing research practices involving multisite studies of sensitive mental health conditions. An important feature is the data's close-to-real-time quality assessment (QA) and quality control (QC). The focus on close-to-real-time QA/QC makes it possible for a subject to redo a testing session, as well as facilitate course corrections to prevent repeating errors in future data acquisition. Watch Dr. Sylvain Bouix discuss his work and this article: https://vimeo.com/1025555648 .

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Conflict of interest statement

Competing interests: A.A. is a cofounder, serves as a member of the Board of Directors, as a scientific adviser, and holds equity in Manifest Technologies, Inc.; and is a coinventor on the following patent: Anticevic A, Murray JD, Ji JL: Systems and Methods for NeuroBehavioral Relationships in Dimensional Geometric Embedding, PCT International Application No. PCT/US2119/022110, filed Mar 13, 2019. D.D. has received honorary funds for one educational seminar for CSL Sequiris. J.K. is consultant to, or receives honoraria and/or travel support and/or speakers bureau: Alkermes, Allergan, Boehringer-Ingelheim, Cerevel, Dainippon Sumitomo, H. Lundbeck, HealthRhythms, HLS Therapeutics, Indivior, Intracellular Therapies, Janssen Pharmaceutical, Johnson & Johnson, Karuna Therapeutics/Bristol Meyer-Squibb, L.B. Pharmaceuticals, Mapi, Maplight, Merck, Minerva, Neurocrine, Newron, Novartis, NW PharmaTech, Otsuka, Roche, Saladax, Sunovion, Teva. He is on the advisory boards of Alkermes, Boehringer-Ingelheim, Cerevel, Click Therapeutics, Karuna/BMS, Lundbeck, Merck, Newron, Novartis, Otsuka, Sumitomo, Teva, Terran. He receives grant support from Lundbeck, Janssen, Otsuka, Sunovion. He is a shareholder of Cerevel (public/stock), HealthRhythms (private/stock options), Karuna/BMS (public), L.B. Pharmaceuticals, Inc. (private/stock options), North Shore Therapeutics (private/stock), Vanguard Research Group (private/40% owner). P.F.P. has received research funds or personal fees from Lundbeck, Angelini, Menarini, Sunovion, Boehringer Ingelheim, Proxymm Science, Otsuka, outside the current study. P.J.M. has been a consultant for Otsuka and TEVA. R.S.K. has been consulting for Alkermes, Boehringer-Ingelheim. S.W.W. has received speaking fees from the American Psychiatric Association and from Medscape Features. He has been granted US patent no. 8492418 B2 for a method of treating prodromal schizophrenia with glycine agonizts. He owns stock in N.W. PharmaTech. J.T. is advisor to Precision Mental Wellness. Research support from Otsuka. K.A. is on the CIAS Advisory Board for Boehringer Ingelheim. Z.T. is a consultant for Manifest Technologies. All other authors declare no Competing Financial or Non-Financial Interests.

Figures

Fig. 1
Fig. 1. Diagram of the AMP SCZ data management system and flow.
Data are captured, aggregated and de-identified within each research network before being transferred for processing and curation to the DPACC.
Fig. 2
Fig. 2
The PHOENIX directory structure categorizing multimodal data depending on whether they contain sensitive information.
Fig. 3
Fig. 3. EEG quality checking tool.
Raters are presented with a set of charts (e.g., line noise and response measures), which inform the QC rating captured in the application.
Fig. 4
Fig. 4
Total number of form data variables received over time.

References

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