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Temporal Investigation of Multimodal Elements

An Observational, Longitudinal Study to Characterize the Dynamic Structure of Molecular and Digital Health Data in Healthy Older Adults

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07107386
Acronym
TIME
Enrollment
120
Registered
2025-08-06
Start date
2025-06-15
Completion date
2028-06-30
Last updated
2025-08-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health

Brief summary

The TIME Study is a research project aiming to understand the body's natural rhythms. The goal is to see how daily and weekly changes in our bodies-from what's happening at a molecular level to data from wearable devices-are connected. What is the study about? This study is trying to create a detailed map of how a person's body changes over time. By looking at information from blood, urine, and other samples, as well as data from smartwatches and other devices, researchers want to learn how our bodies' natural cycles work in healthy older adults. The long-term goal is to use this knowledge to help develop more personalized healthcare in the future. Who can participate? The study is looking for healthy adults, age 55 or older, who have a smartphone and are able to travel to the Buck Institute in Novato, California, for study visits. Participants will be asked to: Attend weekly visits over 11 weeks to provide blood and other samples. Wear health-tracking devices like a smart ring and watch. Use a smartphone app to answer questions about their daily routines. Complete two challenge tests, including drinking a glucose solution and exercising on a stationary bicycle. Return for follow-up visits after 6 and 12 months. Are there any risks or benefits? Benefits: There are no direct health benefits for participants. However, the information gained will help scientists create better diagnostic tools and treatments for future generations. Risks: The main risks are minor discomfort from things like blood draws or skin irritation from the wearable devices. All personal information and data are kept private and secure.

Interventions

None listed

Sponsors

Phenome Health
CollaboratorUNKNOWN
Buck Institute for Research on Aging
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
55 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Healthy adults aged 55 years or older. * Own a smartphone capable of running study-specific apps. * Willing and able to attend in-person visits at the Buck Institute in Novato, CA. * Reside in the Pacific or Mountain Time Zones. * Able to speak, read, and write English. * Willing to wear study devices continuously and allow researchers access to all data. * Able to provide informed consent.

Exclusion criteria

* Hospitalization within the last 3 months. * Needing assistance with daily living activities. * Working night or irregular shifts. * Certain musculoskeletal, pulmonary, or cardiovascular conditions. * Uncontrolled high blood pressure (BP \> 180/100 mmHg). * Bleeding disorders, anemia requiring treatment, or recent blood donation. * Poor vein access. * Unstable health conditions. * Chronic antibiotic use. * Certain psychiatric disorders. * Use of excluded medications, supplements, or products, including certain antibiotics or frequent sleep aids.

Design outcomes

Primary

MeasureTime frameDescription
Generation of a longitudinal multi-omic and digital health dataset characterizing biorhythms in older adults12 monthsEstablish a publicly shareable reference dataset integrating blood-based proteomic, metabolomic, and lipidomic profiles with continuous digital health data and microbiome samples from healthy older adults over time, capturing daily, weekly, and perturbation-induced physiological dynamics.

Secondary

MeasureTime frameDescription
Characterization of associations between molecular biomarkers and digital health data across time12 monthsIdentify and quantify temporal correlations between blood-derived molecular biomarkers and physiological signals collected via wearable devices, including responses to standardized challenges.

Countries

United States

Contacts

Primary ContactBrianna Stubbs, Research Assistant Professor, PhD.
TIME-Study@buckinstitute.org(415) 209-2072
Backup ContactAlison Le, Project Manager
TIME-Study@buckinstitute.org

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026