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问题、挑战与前景:精准医学的视角

Problems, challenges and promises: perspectives on precision medicine.

作者信息

Duffy David J

出版信息

Brief Bioinform. 2016 May;17(3):494-504. doi: 10.1093/bib/bbv060. Epub 2015 Aug 5.

Abstract

The 'precision medicine (systems medicine)' concept promises to achieve a shift to future healthcare systems with a more proactive and predictive approach to medicine, where the emphasis is on disease prevention rather than the treatment of symptoms. The individualization of treatment for each patient will be at the centre of this approach, with all of a patient's medical data being computationally integrated and accessible. Precision medicine is being rapidly embraced by biomedical researchers, pioneering clinicians and scientific funding programmes in both the European Union (EU) and USA. Precision medicine is a key component of both Horizon 2020 (the EU Framework Programme for Research and Innovation) and the White House's Precision Medicine Initiative. Precision medicine promises to revolutionize patient care and treatment decisions. However, the participants in precision medicine are faced with a considerable central challenge. Greater volumes of data from a wider variety of sources are being generated and analysed than ever before; yet, this heterogeneous information must be integrated and incorporated into personalized predictive models, the output of which must be intelligible to non-computationally trained clinicians. Drawing primarily from the field of 'oncology', this article will introduce key concepts and challenges of precision medicine and some of the approaches currently being implemented to overcome these challenges. Finally, this article also covers the criticisms of precision medicine overpromising on its potential to transform patient care.

摘要

“精准医学(系统医学)”概念有望实现向未来医疗保健系统的转变,采用更积极主动和具有预测性的医学方法,重点在于疾病预防而非症状治疗。针对每位患者的个性化治疗将是这种方法的核心,患者的所有医疗数据都将通过计算进行整合并可供访问。精准医学正迅速得到欧盟和美国的生物医学研究人员、开拓性临床医生以及科学资助项目的认可。精准医学是“地平线2020”(欧盟研究与创新框架计划)和白宫精准医学计划的关键组成部分。精准医学有望彻底改变患者护理和治疗决策。然而,精准医学的参与者面临着一个相当核心的挑战。与以往相比,来自更广泛来源的大量数据正在被生成和分析;然而,这种异构信息必须进行整合并纳入个性化预测模型,而这些模型的输出结果必须让未接受过计算培训的临床医生能够理解。本文主要借鉴“肿瘤学”领域的内容,将介绍精准医学的关键概念和挑战,以及目前为克服这些挑战而正在实施的一些方法。最后,本文还涵盖了对精准医学在改变患者护理潜力方面过度承诺的批评。

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