Using Medical Big Data to Develop Personalized Medicine for Dry Eye Disease
Using Medical Big Data to Develop Personalized Medicine for Dry Eye Disease
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DOI：
10.1097/ico.0000000000002500
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发表时间：
2020-11-01
期刊：
影响因子：
2.8
通讯作者：
Murakami, Akira
中科院分区：
文献类型：
--
作者：
Inomata, Takenori;Sung, Jaemyoung;Murakami, Akira
干眼病（DED）是一种慢性、多因素的眼表疾病，具有多种病因，导致泪膜不稳定。在全球范围内，随着社会老龄化和数字设备的日常使用，DED的患病率预计将增加。不幸的是，医疗领域目前还没有准备好满足DED患者的医疗需求。尚未确定无创、可靠和易于重现的生物标志物，目前DED的主要治疗依赖于使用滴眼液缓解症状，没有有效的预防性治疗。医学大数据分析，从多组学研究和移动的健康应用程序中挖掘信息，可能为管理慢性疾病（如DED）提供解决方案。基于OMIC的个体生理状态数据可用于预防高危疾病、准确诊断疾病和改善患者预后。移动的健康应用使得能够通过个人设备便携地收集真实世界的医疗数据和生物信号。总之，这些数据为各种眼表疾病和其他目前缺乏精准医学成分的病理学的个性化治疗奠定了坚实的基础。为了全面实施个性化和精准医疗，传统的聚合医疗数据不应直接应用于个人，而不应对个人病因，表型，表现和症状进行调整。
Dry eye disease (DED) is a chronic, multifactorial ocular surface disorder with multiple etiologies that results in tear film instability. Globally, the prevalence of DED is expected to increase with an aging society and daily use of digital devices. Unfortunately, the medical field is currently unprepared to meet the medical needs of patients with DED. Noninvasive, reliable, and readily reproducible biomarkers have not yet been identified, and the current mainstay treatment for DED relies on symptom alleviation using eye drops with no effective preventative therapies available. Medical big data analyses, mining information from multiomics studies and mobile health applications, may offer a solution for managing chronic conditions such as DED. Omics-based data on individual physiologic status may be leveraged to prevent high-risk diseases, accurately diagnose illness, and improve patient prognosis. Mobile health applications enable the portable collection of real-world medical data and biosignals through personal devices. Together, these data lay a robust foundation for personalized treatments for various ocular surface diseases and other pathologies that currently lack the components of precision medicine. To fully implement personalized and precision medicine, traditional aggregate medical data should not be applied directly to individuals without adjustments for personal etiology, phenotype, presentation, and symptoms.