Type 2 DiabetesAI-READINCT06002048
AI Ready and Exploratory Atlas for Diabetes Insights
An observational study of Type 2 Diabetes, run by University of Washington at 3 sites in United States.
Trial summary
The study will collect a cross-sectional dataset of 4000 people across the US from diverse racial/ethnic groups who are either 1) healthy, or 2) belong in one of the three stages of diabetes severity (pre-diabetes/diet controlled, oral medication and/or non-insulin-injectable medication controlled, or insulin… Read more about this study
- Who is it for?
- Ages 40 to 85 years
- Conditions the study is for
- Type 2 Diabetes
- Type of treatment
- Pill or oral medicine, Injection or infusion
- How many people
- 4,000 participants
- Where
- 3 sitesUnited States
- Study dates
- 19 Jul 2023to 1 Jan 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients will be recruited into one of four groups: 1) healthy/no diabetes, 2) pre-diabetes/borderline diabetes/diet-controlled diabetes, 3) oral medication and/or non-insulin injectable medication controlled type 2 diabetes, or 4) insulin dependent type 2 diabetes. The investigators aim to recruit approximately 1000 patients into each of the four groups. Patients will be recruited from University of Washington (UW), University of California at San Diego (UCSD), and University of Alabama at Birmingham (UAB). The study aims to recruit 1,000 subjects from each of the following racial and ethnic groups: white, Asian, Hispanic, and Black. Subjects will be age- and sex-matched within and between groups.
Who may be able to join
- Adults (≥ 40 years old)
- Patients with and without type 2 diabetes
- Able to provide consent
- Must be able to read and speak English
Who cannot join
- Adults older than 85 years of age
- Pregnancy
- Gestational diabetes
- Type 1 diabetes
Trial locations and contacts
3 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States3 sites
University of Alabama, Birmingham
Birmingham, Alabama, 35233
UC San Diego
San Diego, California, 92093
University of Washington
Seattle, Washington, 98109
About this study
The study will collect a cross-sectional dataset of 4000 people across the US from diverse racial/ethnic groups who are either 1) healthy, or 2) belong in one of the three stages of diabetes severity (pre-diabetes/diet controlled, oral medication and/or non-insulin-injectable medication controlled, or insulin dependent), forming a total of four groups of patients. Clinical data (social determinants of health surveys, continuous glucose monitoring data, biomarkers, genetic data, retinal imaging, cognitive testing, etc.) will be collected. The purpose of this project is data generation to allow future creation of artificial intelligence/machine learning (AI/ML) algorithms aimed at defining disease trajectories and underlying genetic links in different racial/ethnic cohorts. A smaller subgroup of participants will be invited to come for a follow-up visit in year 4 of the project (longitudinal arm of the study). Data will be placed in an open-source repository and samples will be sent to the study sample repository and used for future research.
Read the detailed description
The Artificial Intelligence Ready and Exploratory Atlas for Diabetes Insights (AI-READI) project seeks to create a flagship ethically-sourced dataset to enable future generations of artificial intelligence/machine learning (AI/ML) research to provide critical insights into type 2 diabetes mellitus (T2DM), including salutogenic pathways to return to health. The ability to understand and affect the course of complex, multi-organ diseases such as T2DM has been limited by a lack of well-designed, high quality, large, and inclusive multimodal datasets. The AI-READI team of investigators will aim to collect a cross-sectional dataset of 4,000 people and longitudinal data from 10% of the study cohort across the US. The study cohort will be balanced for self-reported race/ethnicity, gender, and diabetes disease stage. Data collection will be specifically designed to permit downstream pseudo-time manifold analysis, an approach used to predict disease trajectories by collecting and learning from complex, multimodal data from participants with differing disease severity (normal to insulin-dependent T2DM). The long-term objective for this project is to develop a foundational dataset in T2DM, agnostic to existing classification criteria or biases, which can be used to reconstruct a temporal atlas of T2DM development and reversal towards health (i.e., salutogenesis). Six cross-disciplinary project modules involving teams located across eight institutions will work together to develop this flagship dataset. Data will be optimized for downstream AI/ML research and made publicly available. This project will also create a roadmap for ethical and equitable research that focuses on the diversity of the research participants and the workforce involved at all stages of the research process (study design and data collection, curation, analysis, and sharing and collaboration).
- Conditions
- Type 2 Diabetes
- Keywords
- Machine Learning, Type 2 Diabetes, Retinal Imaging, Data Sharing, Equitable Data Collection
- Medical subject headings
- Diabetes Mellitus, Type 2
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Healthy | Participants who do not have Type 1 or Type 2 Diabetes | |
| Pre-diabetes/Diet Controlled | Participants with pre-Type 2 Diabetes and those with Type 2 Diabetes whose blood sugar is controlled by diet | |
| Oral Medication and/or Non-insulin-injectable Medication Controlled | Participants with Type 2 Diabetes whose blood sugar is controlled by oral or injectable medications other than insulin | |
| Insulin Dependent | Participants with Type 2 Diabetes whose blood sugar is controlled by insulin |
What is being measured
The primary outcome is the main question the study is designed to answer.
Best-corrected visual acuity
Both photopic and mesopic for right and left eyes individually
Measured: July 19, 2023-January 1, 2027
Contrast Sensitivity
Both photopic and mesopic for right and left eyes individually
Measured: July 19, 2023-January 1, 2027
Optical coherence tomography (OCT)
Measured: July 19, 2023-January 1, 2027
fundus photography
Measured: July 19, 2023-January 1, 2027
fluorescence lifetime imaging ophthalmoscopy (FLIO)
Measured: July 19, 2023-January 1, 2027
optical coherence tomography angiography (OCTA)
Measured: July 19, 2023-January 1, 2027
Continuous Glucose Monitoring
Participants wear the Dexcom G6 Pro for 10 days
Measured: July 19, 2023-January 1, 2027
Home humidity
Measured: July 19, 2023-January 1, 2027
Home temperature
measured in Fahrenheit
Measured: July 19, 2023-January 1, 2027
Volatile Organic Compounds (VOC) in home
Measured: July 19, 2023-January 1, 2027
Fine particulate matter that are 2.5 microns or less in diameter (PM2. 5) in home
Measured: July 19, 2023-January 1, 2027
Montreal Cognitive Assessment (MoCA)
Testing memory and cognitive function. Scores range from 0-30, with scores above 26 indicating normal functioning.
Measured: July 19, 2023-January 1, 2027
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Aug 2023
- Study start19 Jul 2023
- Primary completion1 Jan 2027 (estimated)
- Study completion1 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Type 2 DiabetesStudies of the same condition, open and under way.
- More trials run by University of WashingtonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 4,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Washington
- Sponsor type
- University, hospital or other
- Collaborators
- National Institutes of Health (NIH)
- Responsible party
- Principal investigator, Aaron Y Lee, University of Washington
- Investigators
- Aaron Lee, Principal investigator, University of Washington
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06002048
- Sponsor's protocol ID
- STUDY00016228
- Other IDs
- 3OT2OD032644-01S3
- Acronym
- AI-READI
- Status last verified
- Apr 2025
- First submitted
- 24 Jul 2023
- Last updated
- 6 Apr 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI Ready and Exploratory Atlas for Diabetes Insights
- ClinicalTrials.gov ID
- NCT06002048
- Acronym / sponsor ID
- AI-READI / STUDY00016228
- Conditions
- Type 2 Diabetes
- Keywords
- Machine Learning, Type 2 Diabetes, Retinal Imaging, Data Sharing, Equitable Data Collection
- Study type
- Observational
- Recruitment status
- Enrolling by invitation
- Enrolment
- 4,000 participants (estimated)
- Lead sponsor
- University of WashingtonUniversity, hospital or other
- Collaborators
- National Institutes of Health (NIH)
- Study start
- 19 Jul 2023 (actual)
- Primary completion
- 1 Jan 2027 (estimated)
- Study completion
- 1 Jan 2027 (estimated)
- First posted
- 21 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The study will collect a cross-sectional dataset of 4000 people across the US from diverse racial/ethnic groups who are either 1) healthy, or 2) belong in one of the three stages of diabetes severity (pre-diabetes/diet controlled, oral medication and/or non-insulin-injectable medication controlled, or insulin dependent), forming a total of four groups of patients. Clinical data (social determinants of health surveys, continuous glucose monitoring data, biomarkers, genetic data, retinal imaging, cognitive testing, etc.) will be collected. The purpose of this project is data generation to allow future creation of artificial intelligence/machine learning (AI/ML) algorithms aimed at defining disease trajectories and underlying genetic links in different racial/ethnic cohorts. A smaller subgroup of participants will be invited to come for a follow-up visit in year 4 of the project (longitudinal arm of the study). Data will be placed in an open-source repository and samples will be sent to the study sample repository and used for future research.
Detailed description
The Artificial Intelligence Ready and Exploratory Atlas for Diabetes Insights (AI-READI) project seeks to create a flagship ethically-sourced dataset to enable future generations of artificial intelligence/machine learning (AI/ML) research to provide critical insights into type 2 diabetes mellitus (T2DM), including salutogenic pathways to return to health. The ability to understand and affect the course of complex, multi-organ diseases such as T2DM has been limited by a lack of well-designed, high quality, large, and inclusive multimodal datasets. The AI-READI team of investigators will aim to collect a cross-sectional dataset of 4,000 people and longitudinal data from 10% of the study cohort across the US. The study cohort will be balanced for self-reported race/ethnicity, gender, and diabetes disease stage. Data collection will be specifically designed to permit downstream pseudo-time manifold analysis, an approach used to predict disease trajectories by collecting and learning from complex, multimodal data from participants with differing disease severity (normal to insulin-dependent T2DM). The long-term objective for this project is to develop a foundational dataset in T2DM, agnostic to existing classification criteria or biases, which can be used to reconstruct a temporal atlas of T2DM development and reversal towards health (i.e., salutogenesis). Six cross-disciplinary project modules involving teams located across eight institutions will work together to develop this flagship dataset. Data will be optimized for downstream AI/ML research and made publicly available. This project will also create a roadmap for ethical and equitable research that focuses on the diversity of the research participants and the workforce involved at all stages of the research process (study design and data collection, curation, analysis, and sharing and collaboration).
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Healthy | – | –Participants who do not have Type 1 or Type 2 Diabetes |
| Pre-diabetes/Diet Controlled | – | –Participants with pre-Type 2 Diabetes and those with Type 2 Diabetes whose blood sugar is controlled by diet |
| Oral Medication and/or Non-insulin-injectable Medication Controlled | – | –Participants with Type 2 Diabetes whose blood sugar is controlled by oral or injectable medications other than insulin |
| Insulin Dependent | – | –Participants with Type 2 Diabetes whose blood sugar is controlled by insulin |
Who may qualify
- Ages
- 40 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients will be recruited into one of four groups: 1) healthy/no diabetes, 2) pre-diabetes/borderline diabetes/diet-controlled diabetes, 3) oral medication and/or non-insulin injectable medication controlled type 2 diabetes, or 4) insulin dependent type 2 diabetes. The investigators aim to recruit approximately 1000 patients into each of the four groups. Patients will be recruited from University of Washington (UW), University of California at San Diego (UCSD), and University of Alabama at Birmingham (UAB). The study aims to recruit 1,000 subjects from each of the following racial and ethnic groups: white, Asian, Hispanic, and Black. Subjects will be age- and sex-matched within and between groups.
Key inclusion criteria (4 listed)
- Adults (≥ 40 years old)
- Patients with and without type 2 diabetes
- Able to provide consent
- Must be able to read and speak English
Key exclusion criteria (4 listed)
- Adults older than 85 years of age
- Pregnancy
- Gestational diabetes
- Type 1 diabetes
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Best-corrected visual acuity
Time frame: July 19, 2023-January 1, 2027
Both photopic and mesopic for right and left eyes individually
Contrast Sensitivity
Time frame: July 19, 2023-January 1, 2027
Both photopic and mesopic for right and left eyes individually
Optical coherence tomography (OCT)
Time frame: July 19, 2023-January 1, 2027
fundus photography
Time frame: July 19, 2023-January 1, 2027
fluorescence lifetime imaging ophthalmoscopy (FLIO)
Time frame: July 19, 2023-January 1, 2027
optical coherence tomography angiography (OCTA)
Time frame: July 19, 2023-January 1, 2027
Continuous Glucose Monitoring
Time frame: July 19, 2023-January 1, 2027
Participants wear the Dexcom G6 Pro for 10 days
Home humidity
Time frame: July 19, 2023-January 1, 2027
Home temperature
Time frame: July 19, 2023-January 1, 2027
measured in Fahrenheit
Volatile Organic Compounds (VOC) in home
Time frame: July 19, 2023-January 1, 2027
Fine particulate matter that are 2.5 microns or less in diameter (PM2. 5) in home
Time frame: July 19, 2023-January 1, 2027
Montreal Cognitive Assessment (MoCA)
Time frame: July 19, 2023-January 1, 2027
Testing memory and cognitive function. Scores range from 0-30, with scores above 26 indicating normal functioning.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Apr 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Aaron Lee principal investigator
University of Washington
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Type 2 Diabetes, run by University of Washington at 3 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 6 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Best-corrected visual acuity (time frame: July 19, 2023-January 1, 2027). The study lists 12 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Apr 2025.