• Medientyp: E-Artikel
  • Titel: Community Consensus Guidelines to Support FAIR Data Standards in Clinical Research Studies in Primary Mitochondrial Disease
  • Beteiligte: Karaa, Amel; MacMullen, Laura E.; Campbell, John C.; Christodoulou, John; Cohen, Bruce H.; Klopstock, Thomas; Koga, Yasutoshi; Lamperti, Costanza; van Maanen, Rob; McFarland, Robert; Parikh, Sumit; Rahman, Shamima; Scaglia, Fernando; Sherman, Alexander V.; Yeske, Philip; Falk, Marni J.
  • Erschienen: Wiley, 2022
  • Erschienen in: Advanced Genetics, 3 (2022) 1
  • Sprache: Englisch
  • DOI: 10.1002/ggn2.202100047
  • ISSN: 2641-6573
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  • Beschreibung: AbstractPrimary mitochondrial diseases (PMD) are genetic disorders with extensive clinical and molecular heterogeneity where therapeutic development efforts have faced multiple challenges. Clinical trial design, outcome measure selection, lack of reliable biomarkers, and deficiencies in long‐term natural history data sets remain substantial challenges in the increasingly active PMD therapeutic development space. Developing “FAIR” (findable, accessible, interoperable, reusable) data standards to make data sharable and building a more transparent community data sharing paradigm to access clinical research metadata are the first steps to address these challenges. This collaborative community effort describes the current landscape of PMD clinical research data resources available for sharing, obstacles, and opportunities, including ways to incentivize and encourage data sharing among diverse stakeholders. This work highlights the importance of, and challenges to, developing a unified system that enables clinical research structured data sharing and supports harmonized data deposition standards across clinical consortia and research groups. The goal of these efforts is to improve the efficiency and effectiveness of drug development and improve understanding of the natural history of PMD. This initiative aims to maximize the benefit for PMD patients, research, industry, and other stakeholders while acknowledging challenges related to differing needs and international policies on data privacy, security, management, and oversight.
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