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Measuring and Predicting Glycemic Response to Food in Patients With Type 1 Diabetes

Measuring and Predicting Glycemic Response to Food in Patients With Type 1 Diabetes

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT02919839
Enrollment
200
Registered
2016-09-29
Start date
2016-09-30
Completion date
2019-01-31
Last updated
2016-09-29

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

Conditions

Personalized Medicine in Type 1 Diabetes

Brief summary

Personalized medicine methods in the management of type 1 diabetes

Detailed description

This proposal joins together clinical practitioners, biologists, and computer scientists to set up the infrastructure for research that will facilitate, for the first time, the use of big-data, machine-learning approaches in the application of personalized medicine methods in the management of type 1 diabetes mellitus. We will model the clinical, microbial, and nutritional factors underlying the variability in glycemic response to food in this population; develop algorithms for prediction of this response and for the accurate administration of insulin, assisting the clinical management of the disease and discover intervention targets in the gut microbiome aimed at improving glycemic control.

Interventions

OTHERnon-Interventional

Sponsors

Weizmann Institute of Science
CollaboratorOTHER
Dr. Orit Hamiel
Lead SponsorOTHER_GOV

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
2 Years to No maximum
Healthy volunteers
No

Inclusion criteria

over one year of diagnostic with T1DM.

Exclusion criteria

Drug related diabetes. genetical diabetes.

Design outcomes

Primary

MeasureTime frame
blood glucose2 weeks

Contacts

Primary ContactOrit P Hamiel, Prof.
Orit.Hamiel@sheba.health.gov.il97235305015
Backup ContactElinor Mauda
Elinor.Mauda@sheba.health.gov.il97235305015

Outcome results

None listed

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