Wearable technology and systems modeling for personalized chronotherapy

被引:38
作者
Kim, Dae Wook [1 ]
Zavala, Eder [2 ]
Kim, Jae Kyoung [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Dept Math Sci, Daejeon 34141, South Korea
[2] Univ Birmingham, Inst Metab & Syst Res, Ctr Syst Modelling & Quantitat Biomed, Edgbaston B15 2TT, England
基金
新加坡国家研究基金会; 英国医学研究理事会; 英国工程与自然科学研究理事会;
关键词
Chronotherapy; Mathematical model; Personalized medicine; Wearables; Circadian rhythms; Ultradian rhythms; Systems pharmacology model; Machine learning; Circadian medicine; COLORECTAL-CANCER; MELATONIN; SLEEP; PHASE; LIGHT; RHYTHMS;
D O I
10.1016/j.coisb.2020.07.007
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Chronotherapy is a pharmaceutical intervention that considers the patient's internal circadian time to adjust dosing time. Although it can dramatically improve drug efficacy and reduce toxicity, the large variability in internal time across and within individuals has prevented chronotherapies from progressing beyond clinical trials. To translate chronotherapy developments into a real-world outpatient clinical scenario, a personalized characterization and analysis of a patient's internal time is essential. Here, we describe recent advances in wearable technology that enable real-time high-resolution tracking of circadian and ultradian rhythms. We discuss how integrating wearable data into analysis platforms including systems modeling and machine learning can pave the way toward personalized adaptive chronotherapy.
引用
收藏
页码:9 / 15
页数:7
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