Institute for Next Generation Healthcare Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, NY 10029, USA.
Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA 94158, USA.
Hum Mol Genet. 2018 May 1;27(R1):R56-R62. doi: 10.1093/hmg/ddy114.
Precision medicine can utilize new techniques in order to more effectively translate research findings into clinical practice. In this article, we first explore the limitations of traditional study designs, which stem from (to name a few): massive cost for the assembly of large patient cohorts; non-representative patient data; and the astounding complexity of human biology. Second, we propose that harnessing electronic health records and mobile device biometrics coupled to longitudinal data may prove to be a solution to many of these problems by capturing a 'real world' phenotype. We envision that future biomedical research utilizing more precise approaches to patient care will utilize continuous and longitudinal data sources.
精准医学可以利用新技术,更有效地将研究成果转化为临床实践。在本文中,我们首先探讨了传统研究设计的局限性,这些局限性源于(仅举几例):为组建大型患者队列而付出的巨大成本;非代表性的患者数据;以及人类生物学的惊人复杂性。其次,我们提出,利用电子健康记录和移动设备生物识别技术加上纵向数据,通过捕捉“真实世界”的表型,可能是解决这些问题的一种方法。我们设想,未来利用更精确的患者护理方法的生物医学研究将利用连续和纵向数据源。