Real-time

Real-time integrates urine metabolomics with biohealth smartphone application data to enable continuous assessment of metabolic phenotypes for personalized health monitoring.


Key Features:

  • Integration with Digital Medicine: Integrates biohealth smartphone application data with continuous metabolic phenotypes derived from urine metabolites to combine molecular phenotypes with quantitative lifestyle measurements.
  • Continuous Monitoring: Enables real-time tracking of physiological changes through continuous measurement of urine metabolites to capture biological consequences of human behavior.
  • Lifestyle Factor Analysis: Monitors nutrition, drug metabolism, exercise, and sleep by analyzing urine metabolites to assess dynamic lifestyle impacts on metabolism.
  • Data Visualization: Provides visualization of observational study metabolic data to represent complex metabolite profiles and lifestyle metrics.

Scientific Applications:

  • Observational study of human metabolism: Applies integration of urine metabolite profiles and smartphone-tracked lifestyle metrics in an observational study involving two healthy subjects to link daily behaviors to metabolic changes.
  • Personalized and preventive medicine research: Supports research into tailored interventions and preventive strategies by capturing the biological impact of daily behaviors on metabolic phenotypes.

Methodology:

Urine samples are collected and analyzed for metabolite profiles which are correlated and integrated with biohealth smartphone application lifestyle metrics.

Topics

Details

Programming Languages:
Python
Added:
1/14/2020
Last Updated:
1/15/2021

Operations

Publications

Miller IJ, Peters SR, Overmyer KA, Paulson BR, Westphall MS, Coon JJ. Real-time health monitoring through urine metabolomics. npj Digital Medicine. 2019;2(1). doi:10.1038/s41746-019-0185-y. PMID:31728416. PMCID:PMC6848197.

PMID: 31728416
PMCID: PMC6848197
Funding: - U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences: R35GM118110