Wearable technology and systems modeling for personalized chronotherapy

Dae Wook Kim, Eder Zavala, Jae Kyoung Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
86 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)9-15
Number of pages7
JournalCurrent Opinion in Systems Biology
Volume21
DOIs
Publication statusPublished - 25 Jul 2020

Keywords

  • Chronotherapy
  • Circadian medicine
  • Circadian rhythms
  • Machine learning
  • Mathematical model
  • Personalized medicine
  • Systems pharmacology model
  • Ultradian rhythms
  • Wearables

ASJC Scopus subject areas

  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Drug Discovery
  • Computer Science Applications
  • Applied Mathematics

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