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The Pluripotent Rendering of Clinical Data for Precision Medicine

机译:精密药物临床数据的多能渲染

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Health care and biomedical research are awash in data. Traditional data warehouse methodologies do not scale to this challenge; nor do their schema match the variety of analytic use cases. An alternative model, which shreds data into well-formed constituent data elements, conformant with the emerging CIMI-FHIR standards and stored together with the complete, raw, source data using modern and scalable data utilities such as Hadoop and its derivatives, affords the creation of pluripotent data repositories. Such repositories can be leveraged to generate any number of data marts, registries, and analytic data sets, each of which "just in time " binds an appropriate use-case specific data model. We call this notion PiCaRD: Pluripotent Clinical Repository of Data. We believe such nimble biomedical data management strategies are crucial for Precision Medicine discovery and application.
机译:保健和生物医学研究是令人畏缩的。传统数据仓库方法无法扩展到这一挑战;他们的模式也不符合各种分析用例。一种替代模型,将数据划分为更良好的组成数据元素,符合新兴的CIMI-FHIR标准并使用现代和可扩展的数据公用事业(如Hadoop及其衍生物)提供了完整的原始的源数据,提供了创造多能数据存储库。可以利用这些存储库来生成任何数量的数据集市,注册表和分析数据集,每个数据集和分析数据集是“刚刚及时”绑定适当的用途特定数据模型。我们称此介绍Picard:多能临床数据库数据库。我们认为,这种灵活的生物医学数据管理策略对于精密药物发现和应用至关重要。

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