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Randomized Controlled Trial of Digital Twin Precision Treatment: A Novel Whole Body Digital Twin Enabled Precision Treatment for Type 2 Diabetes (TPT)

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NeuroTherapia, Inc.

Status

Active, not recruiting

Conditions

Type 2 Diabetes

Treatments

Behavioral: Twin Precision Treatment

Study type

Interventional

Funder types

Other

Identifiers

Details and patient eligibility

About

This is a randomized study comparing outcomes of patients diagnosed with Type 2 Diabetes (T2D) who are enrolled into the Twin Health Precision Treatment (TPT) system versus usual care. The study will last for a year with a 1 year optional extension for the TPT arm patients to continue for another year, and for the usual care (UC) patients to cross over to the TPT treatment for a year.

150 patients will be enrolled with 100 being randomized to the TPT arm and 50 being enrolled to the UC arm

Full description

This is a randomized study comparing outcomes of usual care patients diagnosed with Type 2 Diabetes (T2D) with patients diagnosed with T2D enrolled onto Twin Health's TPT system. Twin Precision Treatment (TPT) system utilizes live, exercise and nutrition coaching based on computer algorithm learning to attempt to improve patients overall health and reverse type 2 diabetes (T2D). The TPT system does so by measuring and addressing glucose aberrations associated with meals. Using Whole Body Digital Twin (WBDT) platform powered by Artificial Intelligence (AI) and the Internet of Things (IoT) technologies, the Whole Body Digital Twin platform captures data on up to 174 health markers, up to 3000 daily data points to provide precision nutrition guidance to the patient that precisely balances 87 essential nutrient factors. The platform captures daily weight using Bluetooth scales and captures daily blood pressure, particularly in patients with underlying HTN using Bluetooth blood pressure measurement. Additionally, the Whole Body Digital Twin platform captures daily physical activity and sleep data, and provides precision guidance on activity and sleep for the patient to follow.

The machine learning algorithm is devised to integrate these multi-dimensional data and accurately predict personalized glucose responses. Dietary intake is a central determinant of blood glucose levels, and thus, to achieve optimal glucose levels, it is imperative to make food choices that induce normal postprandial glycemic responses. Thus, the platform will suggest the right food to the right participant at the right time.

Depending on the likes and dislikes of the patient, the Whole Body Digital Twin platform will recommend a meal plan that is balanced across macro, micro and biota nutrients to reduce glucotoxicity and lipotoxicity, which helps in ameliorating inflammation, fatty liver and insulin resistance. This precise management of nutrition, activity and sleep ensures that the average blood glucose of the day will be consistently maintained within the optimal range. The intervention will continuously offer precision nutrition, precision sleep and precision activity recommendations. Nutritional, activity, and sleep counseling will be provided by trained health coaches through the app and via telephone.

In the usual care of type 2 diabetes, glucose-lowering medications are added progressively with lifestyle modification to improve glycemia and optimize glycated hemoglobin values (HbA1c) so as to reduce the risk of developing long-term complications. Standard of care is to take such a glucose-centric approach to T2D management rather than focusing treatment on the underlying root causes of the disease. It is rare to attempt to target remission of the diabetes process since remission occurs in usual care regimens in only a very small percentage of patients with type 2 diabetes (21). Studies that target other metabolic disease states, such as obesity, have been proven to also impact T2D progression and achieve remission states, but these types of approaches are rare in the usual care setting (22). Only three therapeutic approaches have been associated with remission of diabetes: 1. Bariatric surgery, 2. Very Low-Calorie diet, and 3. Ketogenic diet with near elimination of carbohydrate (23). Our study attempts to determine if precision nutritional, activity and sleep guidance associated with the Whole Body Digital Twin (WBDT) platform and Twin Precision Treatment (TPT) can lead to diabetes remission in a population of patients with T2D.

Enrollment

150 patients

Sex

All

Ages

18 to 75 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  1. Men and women between ages 18 and 75
  2. Self-reported duration of Type 2 diabetes less than or equal to 15 Years
  3. Own smartphone and compatible with TPT and sensors (iPhone and android)
  4. Baseline HbA1c of ≥ 7.5% and ≤ 11% or baseline A1c ≥ 6.5% but < 7.5% on any glucose lowering medication (inclusive of Metformin). For patients with a baseline A1c of < 6.5%, the patient must be on at least one glucose lowering medication with or without Metformin.
  5. BMI: ≥ 27 Kg/2
  6. NAFLD Fibrosis Score > -1.00 to be screened and enrolled for additional subset MRE evaluation (optional for patient to consent to MRE evaluation) of liver steatosis/fibrosis (30 patients from TPT group and 15 patients from the Usual Care group)

Exclusion criteria

  1. HbA1C >11%
  2. Type 1 diabetes, latent autoimmune diabetes in adults (LADA), maturity onset diabetes of the young (MODY), pancreatic diabetes, gestational diabetes mellitus, any secondary diabetes by clinical history, or fasting C Peptide < 1 mmol/L or GAD-65 antibody positivity
  3. Currently or in past 3 months receiving an anti-obesity medication or any other medication used for the primary intent of weight loss
  4. History of hospitalization (within the last 12 months) for diabetic ketoacidosis
  5. History of acute coronary syndrome, myocardial infarction, or stroke within the prior 12 months
  6. Inadequate hepatic function as measured by AST/ALT > 3.0 x ULN
  7. Inadequate renal function as measured by eGFR < 30 mL/min/1.73 m2
  8. Current chronic corticosteroid therapy (≥ 5 mg of prednisone per day or an equivalent dose of other anti-inflammatory corticosteroids)
  9. Major surgical procedure or significant traumatic injury within 28 days prior to Enrollment Date
  10. Patients who have undergone or are planning for any bariatric procedure
  11. Pregnant, planning pregnancy in the next 12 months and lactating/nursing females
  12. Any medical or surgical condition that the principal investigator considers making the patient unfit for the trial (e.g., psychiatric disorders, malignancy, etc.)
  13. Mental incapacity or language barrier
  14. Excessive alcohol intake (defined as self-reported greater than or equal to 3 drinks per day)
  15. History of Congestive Heart Failure
  16. Any condition, unwillingness, or inability, not covered by any of the other exclusion criteria, which, in the study clinician's opinion, might jeopardize the subject's safety or compliance with the protocol
  17. Patients who do not have any insurance (government or commercial) coverage at the time of enrollment to avoid confounders in data

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

150 participants in 2 patient groups

Twin Precision Treatment (TPT)
Experimental group
Description:
Twin Precision Treatment (combination of AI and lifestyle coaching)
Treatment:
Behavioral: Twin Precision Treatment
Usual Care (UC)
No Intervention group
Description:
Usual care prescribed by Cleveland Clinic diabetes specialists and primary care physicians

Trial contacts and locations

1

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Central trial contact

Shannon Downie; Ari Smith-Coleman

Data sourced from clinicaltrials.gov

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