Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives

摘要: Compelling research has recently shown that cancer is so heterogeneous single centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology therefore utmost importance. The Findable, Accessible, Interoperable Reusable (FAIR) Principles have been developed define good practices sharing. Motivated by the ambition applying FAIR our own clinical implementations research, we performed a systematic literature review potentially relevant initiatives. For data, suggest using Genomic Commons model as reference it provides field-tested well-documented solution. Regarding classification diagnosis, morphology topography drugs, chose follow World Health Organization standards, i.e. ICD10, ICD-O-3 Anatomical Therapeutic Chemical classifications, respectively. bioinformatics pipeline, Genome Analysis ToolKit Best Practices Docker containers offer coherent solution selected. naming variants, Human Variation Society's standard. IT infrastructure, built centralized participate through federated solutions such Beacon Networks.