Method for prognosticating the treatment of type 1 diabetes - Patent application

Abstract

In one aspect herein, a method is provided for prognosticating the responsiveness of anti-CD3 antibodies in preventing or delaying the onset of type 1 diabetes (T1D).

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Application No. 63 / 246,184, filed September 20, 2021, the entire disclosure of which is incorporated herein by reference.

[0002] Government right to recognition This invention was made with government support awarded by the National Institute of Diabetes and Digestive and Kidney Diseases under grants U01DK127786, R03DK117253, and R01DK121929. The U.S. Government has certain rights in this invention.

[0003] Sequence Listing This specification includes a sequence listing submitted herewith, including a file entitled 178833-011501_ST26.xlm, created on September 18, 2022, and having the following size: 3,396 bytes, the contents of which are incorporated herein by reference.

[0004] Field The present disclosure relates generally to compositions and methods for preventing or delaying the onset of clinical type 1 diabetes (T1D) in at-risk subjects, and more particularly to prognostic values ​​for the use of anti-CD3 antibodies in such prevention or delay. [Background technology]

[0005] Type 1 diabetes (T1D) is caused by autoimmune destruction of insulin-producing beta cells in the islets of Langerhans, resulting in a dependency on exogenous insulin injections for survival. Approximately 16 million Americans have type 1 diabetes, and T1D remains one of the most common childhood diseases after asthma. Despite medical improvements, individuals most affected by T1D are unable to consistently achieve desired glycemic targets. Concerns exist about an increased risk of both morbidity and mortality for individuals with type 1 diabetes. Two recent studies cited a loss of 17.7 years of life in children diagnosed before age 10, and 11 and 13 years of life lost for Scottish men and women, respectively, diagnosed as adults.

[0006] In genetically susceptible individuals, T1D progresses through a subclinical phase before overt hyperglycemia, characterized first by the appearance of autoantibodies (stage 1) and then by glycemic abnormalities (stage 2). In stage 2, the metabolic response to a glycemic load is impaired, but other metabolic indicators, such as glycosylated hemoglobin, are normal and insulin treatment is not required. These immunological / metabolic features identify individuals at high risk for developing clinical disease, with overt hyperglycemia and requiring insulin treatment (stage 3). Several immune interventions have been studied in new-onset clinical T1D and have been shown to slow the decline of beta cell function. One promising treatment is teplizumab, a non-FcR binding anti-CD3 monoclonal antibody, for which several studies have shown that short-term treatment permanently reduces the loss of beta cell function, with observable effects seen for up to seven years after diagnosis and treatment. The drug alters the function of CD8+ T lymphocytes, which are thought to be the key effector cells responsible for the killing of beta cells. Summary of the Invention [Problem to be solved by the invention]

[0007] Currently, interventions initiated prior to clinical diagnosis (i.e., at stages 1 or 2) do not alter progression to clinical stage 3 T1D. Thus, there is a need for treatments that prevent or delay the onset of clinical T1D in high-risk individuals. Additionally, there is a need for improved methods for prognosticating such prevention or delay. [Means for solving the problem]

[0008] In one aspect herein, a method is provided for prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D), comprising administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from an oral glucose tolerance test on a two-dimensional grid, wherein the direction of the change vector toward increased C-peptide and decreased blood glucose is indicative of metabolic improvement.

[0009] In some embodiments, the oral glucose tolerance test comprises a 1 hour oral glucose tolerance test, a 2 hour oral glucose tolerance test, a 4 hour oral glucose tolerance test, or a combination thereof.

[0010] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) comprises administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 1-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0011] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) includes administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 2-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0012] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) comprises administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 4-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0013] In some embodiments, the method further comprises calculating the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) by GCRC. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the directional quadrant of the vector between the baseline coordinate and the 6-month coordinate. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the percent change in blood glucose and the percent change in C-peptide.

[0014] In some embodiments, the therapeutic or prophylactic agent comprises an immunotherapeutic agent. In some embodiments, the immunotherapeutic agent comprises an anti-CD3 antibody or an antigen-binding fragment thereof. In some embodiments, the anti-CD3 antibody is teplizumab, otelixizumab, or foralumab. In one embodiment, the anti-CD3 antibody is teplizumab.

[0015] In some embodiments, an effective amount of a therapeutic or prophylactic agent is between 10 and 1100 micrograms per square meter (mg / m 2 ) by daily subcutaneous (SC) injection or intravenous (IV) infusion or oral administration for 10-14 days. In some embodiments, the effective amount of therapeutic or prophylactic agent is about 9000 mg / m 2 ~About 14000mg / m 2 with anti-CD3 antibodies in a total dose of 10 to 14 days.

[0016] In some embodiments, the method comprises administering to a subject in need thereof 51 mg / m on each of days 1-4. 2 , 103 mg / m 2 , 207 mg / m 2 , and 413 mg / m 2 , and 826 μg / m on each of days 5 to 14. 2 The method includes administering a 14 day course of a single dose of anti-CD3 antibody by IV infusion.

[0017] In some embodiments, the anti-CD3 antibody is teplizumab, otelixizumab, or foralumab. In some embodiments, the anti-CD3 antibody is teplizumab.

[0018] In some embodiments, the subject has T1D stage 1, 2, 3, or 4. In some embodiments, the subject has T1D stage 1 or 2, and the method is used for prognosis for a prophylactic agent in preventing or delaying the onset of T1D.

[0019] A further embodiment relates to a method of prognosticating the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D), comprising administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in the glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from an oral glucose tolerance test on a two-dimensional grid, wherein the direction of the change vector toward increased C-peptide and decreased blood glucose is indicative of metabolic improvement.

[0020] In some embodiments, the method further comprises calculating the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) by GCRC. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the directional quadrant of the vector between the baseline coordinate and the 6-month coordinate. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the percent change in blood glucose and the percent change in C-peptide.

[0021] In some embodiments, the non-clinically diabetic subject has stage 1 or 2 T1D.

[0022] In some embodiments, the oral glucose tolerance test comprises a 1 hour oral glucose tolerance test, a 2 hour oral glucose tolerance test, a 4 hour oral glucose tolerance test, or a combination thereof.

[0023] In some embodiments, a method of prognosing the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 1-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0024] In some embodiments, a method of prognosing the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 2-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0025] In some embodiments, a method of prognosticating the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 4-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0026] In some embodiments, the non-clinically diabetic subject at risk for clinical T1D is a relative of a patient with T1D.

[0027] In some embodiments, the non-clinically diabetic subject at risk for clinical T1D is negative for zinc transporter 8 (ZnT8). In some embodiments, the non-clinically diabetic subject at risk for clinical T1D is HLA-DR4+. In some embodiments, the non-clinically diabetic subject at risk for clinical T1D is not HLA-DR3+. In some embodiments, the non-clinically diabetic subject at risk for clinical T1D is HLA-DR4+ and not HLA-DR3+. In some embodiments, the non-diabetic subject is (1) negative for zinc transporter 8 (ZnT8), (2) HLA-DR4+, and / or (3) not HLA-DR3+.

[0028] In some embodiments, the method further comprises determining that the non-clinically diabetic subject at risk for clinical T1D is negative for zinc transporter 8 (ZnT8) antibodies. In some embodiments, the method further comprises determining that the non-clinically diabetic subject at risk for clinical T1D is HLA-DR4+. In some embodiments, the method further comprises determining that the non-clinically diabetic subject at risk for clinical T1D is HLA-DR4+ and not HLA-DR3+. In some embodiments, the method further comprises determining that the non-clinically diabetic subject at risk for clinical T1D is HLA-DR4+ and not HLA-DR3+. In some embodiments, the method further comprises determining that the non-clinically diabetic subject at risk for clinical T1D is (1) negative for zinc transporter 8 (ZnT8), (2) HLA-DR4+, and / or (3) not HLA-DR3+.

[0029] In some embodiments, a non-clinically diabetic subject at risk for clinical T1D has two or more diabetes-associated autoantibodies selected from islet cytoplasmic antibodies (ICA), insulin autoantibodies (IAA), and antibodies against glutamic acid decarboxylase (GAD), tyrosine phosphatase (IA-2 / ICA512), or ZnT8.

[0030] In some embodiments, a non-clinically diabetic subject at risk for clinical T1D has impaired glucose tolerance in an oral glucose tolerance test (OGTT), hi some embodiments, impaired glucose tolerance in an OGTT is a fasting glucose level of 110-125 mg / dL, or a 2-hour glucose level of ≧140 and <200 mg / dL, or a random glucose level of >200 mg / dL at 30, 60, 90 minutes, or 4 hours after the OGTT.

[0031] In some embodiments, the anti-CD3 antibody is teplizumab, otelixizumab, or foralumab. In some embodiments, the anti-CD3 antibody is teplizumab. In some embodiments, the prophylactically effective amount of the antibody is between 10 and 1100 micrograms per square meter (μg / m 2 ) by subcutaneous (SC) injection or intravenous (IV) infusion or oral administration of an anti-CD3 antibody for a 10-14 day course. In some embodiments, the effective amount of a therapeutic or prophylactic agent is about 9000 μg / m 2 ~Approx. 14000μg / m 2 In some embodiments, the method includes a 10-14 day course of anti-CD3 antibody at a total dose of 51 μg / m on each of days 1-4. 2 , 103 μg / m 2 , 207 μg / m 2 , and 413 μg / m 2 , and 826 μg / m on each of days 5 to 14. 2 by IV infusion for 14 days.

[0032] In some embodiments, the prophylactically effective amount delays the median time to clinical diagnosis of T1D by about 50% to about 90%. In some embodiments, the prophylactically effective amount delays the median time to clinical diagnosis of T1D by at least 12 months, at least 18 months, at least 24 months, at least 36 months, at least 48 months, or at least 60 months.

[0033] In some embodiments, the determination of TIGIT+KLRG1+CD8+ T cells is by flow cytometry.

[0034] In some embodiments, the method further comprises determining a decrease in the percentage of CD8+ T cells expressing the proliferation markers Ki67 and / or CD57. [Brief description of the drawings]

[0035] [Figure 1-1]1A-1F show that the change in GCRC vectors shows opposite directionality between the placebo and teplizumab treatment groups. The change vectors of GCRC for individual participants and the mean value vectors by treatment group were plotted over the intervals from the study visit at baseline (at randomization) to 3 months after treatment (A-D) and from baseline to 6 months after treatment (E-H). A-B: The change in individual GCRC vectors from baseline to 3 months after treatment was plotted for the placebo group (A) and the teplizumab treatment group (B). High risk values ​​(increased blood glucose, decreased C-peptide) are shown as dashed lines, and low risk (decreased blood glucose and increased C-peptide) vectors are shown as bold lines. The quadrant distribution frequency of the vectors was significantly different between the treatment groups (p=0.045). C-D: Mean GCRCs were plotted for the placebo and teplizumab treatment groups at randomization (baseline, shown as solid lines) and at the OGTT performed 3 months into the study (shown as dashed lines). Mean centroid values ​​for blood glucose / C-peptide coordinates were depicted as dots within each GCRC, displaying the change vector. The change in GCRC centroid values ​​over this time period for the placebo group shows a directionality towards the upper left part of the grid, indicating increased blood glucose and decreased C-peptide. The teplizumab treatment group shows an opposite directionality towards the lower right part of the grid, indicating increased C-peptide and decreased blood glucose. E-F: Changes in individual GCRC vectors from baseline to 6 months after treatment were plotted for the placebo (E) and teplizumab (F) treatment groups. The quadrant distribution frequencies of the vectors were significantly different between treatment groups (p=0.0044). G-H: Mean GCRCs were plotted for the placebo and teplizumab treatment groups at randomization (baseline, shown as solid lines) and at the OGTT performed 6 months into the study (shown as dashed lines). Mean centroid values ​​for blood glucose / C-peptide coordinates are depicted as dots within each GCRC, displaying the change vector. The change in GCRC centroid values ​​over this period shows a direction toward the upper left part of the grid for the placebo group, indicating an increase in blood glucose and a decrease in C-peptide.The teplizumab treatment group showed a reverse orientation to the lower right portion of the grid, indicating increased C-peptide and decreased blood glucose. After 3 months: n=29 for placebo; n=41 for teplizumab. After 6 months: n=24 for placebo; n=44 for teplizumab. The absolute frequencies for each vector direction quadrant for each period are presented in Table 1. [Figure 1-2] Continued from Figure 1-1. [Figure 1-3] Continued from Figure 1-2. [Figure 1-4] Continued from Figure 1-3. [Figure 2A] Figure 1 shows statistical evaluation of treatment effect using vector angle within directional quadrant. Individual unadjusted values ​​for change in treatment endpoints A.WQE (Within Quadrant Endpoint) and B.ODE (Ordinal Directional Endpoint) are plotted by treatment group for baseline to 3 months and baseline to 6 months. For treatment group comparison for ODE at 3 months, unadjusted p=0.018 and adjusted p=0.038 for age and BMI. At 6 months, unadjusted p<0.001 and adjusted p=0.002 for age and BMI. For treatment group comparison for WQE at 3 months, unadjusted p=0.026 and adjusted p=0.072 for age and BMI. At 6 months, unadjusted and adjusted p<0.001. *Uncorrected p-value <0.05;***Uncorrected p-value <0.001. At 3 months, n=29 placebo-treated individuals and 41 teplizumab-treated individuals. At 6 months, n=24 placebo-treated individuals and 44 teplizumab-treated individuals. [Figure 2B]Figure 1 shows statistical evaluation of treatment effect using vector angle within directional quadrant. Individual unadjusted values ​​for change in treatment endpoints A.WQE (Within Quadrant Endpoint) and B.ODE (Ordinal Directional Endpoint) are plotted by treatment group for baseline to 3 months and baseline to 6 months. For treatment group comparison for ODE at 3 months, unadjusted p=0.018 and adjusted p=0.038 for age and BMI. At 6 months, unadjusted p<0.001 and adjusted p=0.002 for age and BMI. For treatment group comparison for WQE at 3 months, unadjusted p=0.026 and adjusted p=0.072 for age and BMI. At 6 months, unadjusted and adjusted p<0.001. *Uncorrected p-value <0.05;***Uncorrected p-value <0.001. At 3 months, n=29 placebo-treated individuals and 41 teplizumab-treated individuals. At 6 months, n=24 placebo-treated individuals and 44 teplizumab-treated individuals. [Figure 3A]FIG. 1 shows that the glucose and C-peptide response curve (GCRC) allows visualization and quantification of the relationship between blood glucose and C-peptide as it evolves with the development of type 1 diabetes. A. Hypothetical GCRCs showing typical blood glucose and C-peptide values ​​at 30 (open circles), 60, 90, and 120 minutes (open squares) after an oral glucose tolerance test are plotted for an individual at the time of diagnosis of type 1 diabetes (dashed line) and 6 months prior to diagnosis. The mean value centroid value for blood glucose / C-peptide coordinates is indicated as a dot within each GCRC. A vector showing the change in the mean value GCRC centroid value over this period points towards the upper left part of the grid, indicating an increase in blood glucose and a decrease in C-peptide. B. A conceptual diagram presenting the application of the GCRC vector to create a right triangle that allows the combined application of the direction quadrant of change and the angle generated by the triangle to quantify changes in metabolic function. The calculated angle is the angle between the vector (hypotenuse) and the horizontal side of the right triangle. C. Hypothetical example of vectors for each of the four directional quadrants arising from the center of gravity at baseline when blood glucose and C-peptide values ​​are fixed at 0. Also shown are the calculated angles between the horizontal line and the vectors. [Figure 3B]FIG. 1 shows that the glucose and C-peptide response curve (GCRC) allows visualization and quantification of the relationship between blood glucose and C-peptide as it evolves with the development of type 1 diabetes. A. Hypothetical GCRCs showing typical blood glucose and C-peptide values ​​at 30 (open circles), 60, 90, and 120 minutes (open squares) after an oral glucose tolerance test are plotted for an individual at the time of diagnosis of type 1 diabetes (dashed line) and 6 months prior to diagnosis. The mean value centroid value for blood glucose / C-peptide coordinates is indicated as a dot within each GCRC. A vector showing the change in the mean value GCRC centroid value over this period points towards the upper left part of the grid, indicating an increase in blood glucose and a decrease in C-peptide. B. A conceptual diagram presenting the application of the GCRC vector to create a right triangle that allows the combined application of the direction quadrant of change and the angle generated by the triangle to quantify changes in metabolic function. The calculated angle is the angle between the vector (hypotenuse) and the horizontal side of the right triangle. C. Hypothetical example of vectors for each of the four directional quadrants arising from the center of gravity at baseline when blood glucose and C-peptide values ​​are fixed at 0. Also shown are the calculated angles between the horizontal line and the vectors. [Figure 3C]FIG. 1 shows that the glucose and C-peptide response curve (GCRC) allows visualization and quantification of the relationship between blood glucose and C-peptide as it evolves with the development of type 1 diabetes. A. Hypothetical GCRCs showing typical blood glucose and C-peptide values ​​at 30 (open circles), 60, 90, and 120 minutes (open squares) after an oral glucose tolerance test are plotted for an individual at the time of diagnosis of type 1 diabetes (dashed line) and 6 months prior to diagnosis. The mean value centroid value for blood glucose / C-peptide coordinates is indicated as a dot within each GCRC. A vector showing the change in the mean value GCRC centroid value over this period points towards the upper left part of the grid, indicating an increase in blood glucose and a decrease in C-peptide. B. A conceptual diagram presenting the application of the GCRC vector to create a right triangle that allows the combined application of the direction quadrant of change and the angle generated by the triangle to quantify changes in metabolic function. The calculated angle is the angle between the vector (hypotenuse) and the horizontal side of the right triangle. C. Hypothetical example of vectors for each of the four directional quadrants arising from the center of gravity at baseline when blood glucose and C-peptide values ​​are fixed at 0. Also shown are the calculated angles between the horizontal line and the vectors. [Figure 4]FIG. 1 shows the angles (qangles; indicated in bold) utilized for the WQE based on the orientation quadrants for the GCRC change vectors: metabolic changes over 6 months for blood glucose and C-peptide will fall into one of the four orientation quadrants shown. Each quadrant includes a vector angle calculated between the vector and the horizontal boundary line as well as a vector angle calculated between the vector and the vertical boundary line. For vectors that fall within the top quadrant, the qangle (the angle used to optimize the model for use as an endpoint, indicated in red) was calculated between the vector and the horizontal boundary line. For vectors that fall within the bottom quadrant, the qangle was calculated between the vector and the vertical boundary line. In this example, for RUQ, the vector angle of 62° between the vector and the horizontal axis will be used as the qangle for the development of the WQE. However, for LRQ, the calculated vector angle of 40° (between the vector and the vertical axis) was utilized for the qangle. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0036] The present disclosure relates to a method for prognosticating the responsiveness of a therapeutic or preventive agent for treating type 1 diabetes (T1D).In some embodiments of the present specification, a method for prognosticating the responsiveness of a therapeutic or preventive agent for treating type 1 diabetes (T1D) is provided, which includes the steps of administering the therapeutic or preventive agent to a subject in need thereof; plotting the average blood glucose level and the average C-peptide level by 1-hour oral glucose tolerance test, 2-hour oral glucose tolerance test, or 4-hour oral glucose tolerance test on a two-dimensional grid to construct a glucose and C-peptide response curve (GCRC); visually observing the changes in the shape and movement of the GCRC to determine metabolic improvement; and optionally calculating the Within Quadrant Endpoint (WQE) and Ordinal Directional Endpoint (ODE) by the GCRC.

[0037] In one aspect herein, a method is provided for prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D), comprising administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from an oral glucose tolerance test on a two-dimensional grid, wherein the direction of the change vector toward increased C-peptide and decreased blood glucose is indicative of metabolic improvement.

[0038] In some embodiments, the oral glucose tolerance test comprises a 1 hour oral glucose tolerance test, a 2 hour oral glucose tolerance test, a 4 hour oral glucose tolerance test, or a combination thereof.

[0039] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) comprises administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 1-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0040] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) includes administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 2-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0041] In some embodiments, a method of prognosing responsiveness to a therapeutic or prophylactic agent for treating type 1 diabetes (T1D) includes administering the therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting changes over time in mean blood glucose and mean C-peptide values ​​from a 4-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0042] In some embodiments, the step of determining the change vector of GCRC includes determining average blood glucose and average C-peptide values ​​after administration of a therapeutic or prophylactic agent, and determining baseline average blood glucose and baseline average C-peptide values ​​before administration of the therapeutic or prophylactic agent.

[0043] In some embodiments, the method includes administering a therapeutic or prophylactic agent to a plurality of subjects in need thereof and determining a plurality of change vectors of GCRC. In some embodiments, the frequency of the direction of the plurality of change vectors toward increasing C-peptide and decreasing blood glucose indicates metabolic improvement.

[0044] In some embodiments, the method further comprises plotting the mean GCRC at baseline from a plurality of subjects and the mean GCRC after treatment from a plurality of subjects, determining the mean centroid value at baseline for GCRC at blood glucose / C-peptide coordinates and the mean centroid value after treatment for GCRC after treatment at blood glucose / C-peptide coordinates, and determining the change vector between the mean centroid value at baseline and the mean centroid value after treatment. In some embodiments, the change in the GCRC centroid value and / or the change in the direction of the change vector toward increasing C-peptide and decreasing blood glucose over time indicates metabolic improvement. In some embodiments, the period includes 3 months, 4 months, 5 months, 6 months after administration of the therapeutic or prophylactic agent.

[0045] In some embodiments, the method includes (a) administering a placebo to a first plurality of subjects in need thereof, determining a first plurality of change vectors of GCRC, and determining a frequency of directionality of the first plurality of change vectors toward increased C-peptide and decreased blood glucose; (b) administering a therapeutic or prophylactic agent to a second plurality of subjects in need thereof, determining a second plurality of change vectors of GCRC, and determining a frequency of directionality of the second plurality of change vectors toward increased C-peptide and decreased blood glucose, where a second frequency that is significantly higher than the first frequency is indicative of metabolic improvement.

[0046] In some embodiments, the method further comprises calculating the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) by GCRC. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the directional quadrant of the vector between the baseline coordinate and the 6-month coordinate. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the percent change in blood glucose and the percent change in C-peptide.

[0047] It is noted that the method is used for prognosis of any therapeutic or prophylactic agent in the treatment or prevention of any stage of T1D. T1D is characterized by the destruction of most insulin-producing beta cells through an autoimmune response. Patients with established T1D have residual beta cells that grow but do not reproduce due to the autoimmune disease that destroys them. There are four stages of T1D: Stage 1: multiple (at least two) islet antibodies, normal blood glucose, presymptomatic; Stage 2: multiple islet antibodies, elevated blood glucose, presymptomatic; Stage 3: islet autoimmunity, elevated blood glucose, symptomatic; Stage 4: long-standing type 1 diabetes. In some embodiments of the present disclosure, the method results in the regeneration of beta cells.

[0048] In some embodiments herein, a method is provided for prognosing the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D), comprising administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in the glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from an oral glucose tolerance test on a two-dimensional grid, wherein the direction of the change vector toward increased C-peptide and decreased blood glucose is indicative of metabolic improvement.

[0049] In some embodiments, the oral glucose tolerance test comprises a 1 hour oral glucose tolerance test, a 2 hour oral glucose tolerance test, a 4 hour oral glucose tolerance test, or a combination thereof.

[0050] In some embodiments, a method of prognosing the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 1-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0051] In some embodiments, a method of prognosing the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 2-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0052] In some embodiments, a method of prognosticating the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of clinical type 1 diabetes (T1D) comprises administering a prophylactically effective amount of an anti-CD3 antibody to a non-clinically diabetic subject at risk for clinical T1D; and determining a change vector in a glucose and C-peptide response curve (GCRC) by plotting the change over time in mean blood glucose and mean C-peptide values ​​from a 4-hour oral glucose tolerance test on a two-dimensional grid, wherein a direction of the change vector toward increased C-peptide and decreased blood glucose indicates metabolic improvement.

[0053] In some embodiments, the method further comprises calculating the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) by GCRC. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the directional quadrant of the vector between the baseline coordinate and the 6-month coordinate. In some embodiments, the WQE (Within Quadrant Endpoint) and the ODE (Ordinal Directional Endpoint) are based on the percent change in blood glucose and the percent change in C-peptide.

[0054] In some embodiments, the method further comprises, before or after the administering step, determining that the non-clinically diabetic subject at risk for clinical T1D has more than about 5% to more than about 10% TIGIT+KLRG1+CD8+ T cells among total CD3+ T cells, which indicates successful prevention or delay of onset of clinical T1D. In some embodiments, the method further comprises determining the percentage of TIGIT+KLRG1+CD8+ T cells by flow cytometry. In some embodiments, the method further comprises determining a decrease in the percentage of CD8+ T cells expressing the proliferation markers Ki67 and / or CD57.

[0055] In some embodiments, the non-clinically diabetic subject has stage 1 or 2 T1D.

[0056] In some embodiments, a method of prognosticating the responsiveness of an anti-CD3 antibody in preventing or delaying the onset of type 1 diabetes (T1D) comprises the steps of: providing a non-clinically diabetic subject at risk for T1D; administering a prophylactically effective amount of an anti-CD3 antibody to the non-clinically diabetic subject; constructing a glucose and C-peptide response curve (GCRC) by plotting mean blood glucose and C-peptide values ​​from a 1-hour oral glucose tolerance test, a 2-hour oral glucose tolerance test, or a 4-hour oral glucose tolerance test on a two-dimensional grid; visually observing changes in the shape and movement of the GCRC to determine metabolic improvement; and optionally calculating a Within Quadrant Endpoint (WQE) and an Ordinal Directional Endpoint (ODE) from the GCRC.

[0057] definition As used herein below, certain terms are defined. Additional definitions are provided throughout the application.

[0058] As used herein, the articles "a" and "an" refer to one or more than one grammatical object of the article, e.g., at least one grammatical object. As used herein, the use of the words "a" or "an" when used with the word "comprising" can mean "one," but is also consistent with the meanings "one or more," "at least one," and "one or more than one."

[0059] "About" and "approximately" generally refer to an acceptable degree of error for the quantity being measured given the nature or precision of the measurement. Exemplary degrees of error are within 20 percent (%), typically within 10%, and more typically within 5% of a given range of values. The term "substantially" means greater than 50%, preferably greater than 80%, and most preferably greater than 90% or 95%.

[0060] As used herein, the terms "comprising" or "comprises" are used in reference to compositions, methods, and their respective component(s) present in a given embodiment, but are also open to the inclusion of unspecified elements.

[0061] As used herein, the term "consisting essentially of" refers to elements required for a given embodiment. The term permits the presence of additional elements that do not materially affect the basic and novel characteristic(s) or functional characteristic(s) of this embodiment of the disclosure.

[0062] The term "consisting of" refers to compositions, methods, and their respective components, as described herein, excluding any element not recited in this description of the embodiment.

[0063] As used herein, the term "antibody" is used in the broadest sense and encompasses a variety of antibody structures, including, but not limited to, monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments, so long as they exhibit the desired antigen-binding activity.

[0064] "Antibody fragment" refers to a molecule other than an intact antibody that contains a portion of an intact antibody that binds to the antigen to which the intact antibody binds. Examples of antibody fragments include, but are not limited to, Fv, Fab, cross-Fab, Fab', Fab'-SH, F(ab')2; diabodies; linear antibodies; single-chain antibody molecules (e.g., scFv); and multispecific antibodies formed from antibody fragments.

[0065] As used herein, the term "blood glucose / C-peptide response curve" refers to a plot on a two-dimensional grid of the changes over time in mean blood glucose and mean C-peptide values ​​from a two-hour oral glucose tolerance test.

[0066] In some embodiments, the GCRC is generated by plotting mean blood glucose (y-axis) and mean C-peptide (x-axis) values ​​from the OGTT (at 30, 60, 90, 120 minutes, and after 4 hours) on a two-dimensional grid.

[0067] As used herein, the term "prophylactic agent" refers to a CD3 binding molecule, such as teplizumab, used in the prevention, treatment, management, or amelioration of one or more symptoms of T1D.

[0068] As used herein, the terms "treat", "treatment" and "treating" refer to any indicator of successful treatment or amelioration of an injury, condition, state or symptom (e.g., cognitive impairment), including any objective or subjective parameter, such as sedation; remission; reduction in the severity of a condition; attenuation of symptoms or increasing the tolerability of a symptom, injury, condition or condition to a patient; reduction in the rate of progression of a symptom; reduction in the frequency or duration of a symptom or condition; or, in some circumstances, prevention of onset of a symptom. Treatment or amelioration of a symptom can be based on any objective or subjective parameter, including, for example, the results of a physical examination.

[0069] As used herein, with reference to type 1 diabetes, the term "onset" of disease refers to a patient meeting the criteria established by the American Diabetes Association for the diagnosis of type 1 diabetes (see Mayfield et al., 2006, Am. Fam. Physician, 58:1355-1362).

[0070] As used herein, the terms "prevent," "preventing," and "prevention" refer to the prevention of the onset of one or more symptoms of T1D in a subject resulting from the administration of a prophylactic or therapeutic agent.

[0071] As used herein, a "protocol" includes dosing schedules and dosing regimens. A protocol herein is a method of use, and includes prophylactic and therapeutic protocols. A "dosing regimen" or "course of treatment" can include administration of multiple doses of a therapeutic or prophylactic agent over a period of 1-20 days.

[0072] As used herein, the terms "subject" and "patient" are used interchangeably. As used herein, the terms "subject" and "patient" refer to animals, preferably mammals, including non-primates (e.g., cows, pigs, horses, cats, dogs, rats, and mice) and primates (e.g., monkeys or humans), more preferably humans.

[0073] As used herein, the term "prophylactically effective amount" refers to an amount of teplizumab sufficient to result in delay or prevention of the onset, recurrence, or onset of one or more symptoms of T1D. In some embodiments, a prophylactically effective amount preferably refers to an amount of teplizumab that delays the onset of T1D in a subject by at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%.

[0074] Various aspects of the disclosure are described in further detail below. Additional definitions are set forth throughout the specification.

[0075] Anti-CD3 antibodies and pharmaceutical compositions The terms "anti-CD3 antibody" and "antibody that binds CD3" refer to an antibody or antibody fragment capable of binding to cluster of differentiation 3 (CD3) with sufficient affinity such that the antibody is useful as a prophylactic, diagnostic, and / or therapeutic agent in targeting CD3. In some embodiments, the extent of binding of the antibody to unrelated non-CD3 proteins is less than about 10% of the binding of the antibody to CD3, as measured, for example, by radioimmunoassay (RIA). In some embodiments, an antibody that binds CD3 has a dissociation constant (Kd) of <1 μM, <100 nM, <10 nM, <1 nM, <0.1 nM, <0.01 nM, or <0.001 nM (e.g., 10 -8 M or less, e.g., 10 -8M~10 -13 M, for example, 10 -9 M~10 -13 In some embodiments, the anti-CD3 antibody binds to an epitope of CD3 that is conserved among CD3 from different species.

[0076] In some embodiments, the anti-CD3 antibody can be ChAglyCD3 (Otelixizumab). Otelixizumab is a humanized Fc-nonbinding anti-CD3 that was initially assessed in a Phase 2 study with the Belgian Diabetes Registry (BDR) and then developed by Tolerx, which then partnered with GSK to conduct the Phase 3 DEFEND early-onset T1D trials (NCT00678886, NCT01123083, NCT00763451). Otelixizumab is administered IV by infusion over 8 days. See, e.g., Wiczling et al., J. Clin. Pharmacol. 50(5) (2010) 494-506; Keymeulen et al., N Engl J Med., 2005, 352:2598-608; Keymeulen et al., Diabetologia, 2010, 53:614-23; Hagopian et al., Diabetes, 2013, 62:3901-8; Aronson et al., Diabetes Care, 2014, 37:2746-54; Ambery et al., Diabet Med., 2014, 31:399-402; Bolt et al., Eur. J. Immunol. 1YY, 3, 23:403-411; Vlasakakis et al., Br J Clin See Pharmacol (2019), 85, 704-714; Guglielmi et al., Expert Opinion on Biological Therapy, 16:6, 841-846; Keymeulen et al., N Engl J Med, 2005, 352:2598-608; Keymeulen et al., BLOOD, 2010, Vol. 115, No. 6; Sprangers et al., Immunotherapy (2011), 3(11), 1303-1316; Daifotis et al., Clinical Immunology (2013), 149, 268-278.

[0077] In some embodiments, the anti-CD3 antibody can be visilizumab (also called HuM291; Nuvion). Visilizumab is a humanized anti-CD3 monoclonal antibody characterized by a mutated IgG2 isotype, lack of binding to Fcγ receptors, and the ability to selectively induce apoptosis in activated T cells. Visilizumab has been assessed in patients with graft-versus-host disease (NCT00720629; NCT00032279), as well as ulcerative colitis (NCT00267306) and Crohn's disease (NCT00267709). See, for example, Sandborn et al., Gut, 59(11) (November 2010), 1485-1492, which is incorporated herein by reference.

[0078] In some embodiments, the anti-CD3 antibody can be foralumab, a fully human anti-CD3 monoclonal antibody being developed by Tiziana Life Sciences, PLC in NASH and T2D (NCT03291249). See, e.g., Ogura et al., Clin Immunol., 2017, 183:240-246; Ishikawa et al., Diabetes, 2007, 56(8):2103-9; Wu et al., J Immunol., 2010, 185(6):3401-7, all of which are incorporated by reference herein. Foralumab is a fully human monoclonal antibody that binds to CD3 epsilon (see U.S. Pat. No. 10,688,186, which is incorporated by reference herein in its entirety).

[0079] Teplizumab In some embodiments, the anti-CD3 antibody can be teplizumab. Teplizumab, also known as hOKT3yl (Ala-Ala) (containing alanine at positions 234 and 235), is an anti-CD3 antibody engineered to alter the function of T lymphocytes that mediate the destruction of insulin-producing beta cells of pancreatic islets. Teplizumab binds to an epitope of the CD3ε chain expressed on mature T cells, thereby altering their function. The sequence and composition of teplizumab are disclosed in U.S. Patent Nos. 6,491,916; 8,663,634; and 9,056,906, each of which is incorporated herein by reference in its entirety. The complete sequences of the light and heavy chains are set forth below. The bolded parts are complementarity determining regions.

[0080] Light chain of Teplizumab (SEQ ID NO: 1): [ka]

[0081] Heavy chain of Teplizumab (SEQ ID NO:2): [ka]

[0082] In some embodiments, a pharmaceutical composition is provided herein. Such a composition comprises a prophylactically effective amount of an anti-CD3 antibody and a pharmaceutically acceptable carrier. In some embodiments, the term "pharmaceutically acceptable" means approved by a regulatory agency of the U.S. Federal or State Government or listed in the U.S. Pharmacopeia or other generally recognized pharmacopoeias for use in animals, more particularly approved by such regulatory agencies or listed in such pharmacopoeias for use in humans. The term "carrier" refers to a diluent, adjuvant (e.g., Freund's adjuvant (complete or incomplete)), excipient, or vehicle with which a therapeutic agent is administered. Such pharmaceutical carriers can be sterile liquids, such as water and oils, including oils of petroleum, animal, vegetable, such as peanut oil, soybean oil, mineral oil, sesame oil, or synthetic origin. Water is the preferred carrier when the pharmaceutical composition is administered intravenously. Saline and aqueous dextrose and glycerol solutions are also used as liquid carriers, particularly for injectable solutions.Suitable pharmaceutical excipients include starch, glucose, lactose, sucrose, gelatin, barley, rice, wheat, chalk, silica gel, sodium stearate, glycerol monostearate, talc, sodium chloride, nonfat dry milk, glycerol, propylene, glycol, water, ethanol, etc. (see, for example, "Handbook of Pharmaceutical Excipients," edited by Arthur H. Kibbe, 2000, Am. Pharmaceutical Association, Washington, DC, which is incorporated herein by reference in its entirety).

[0083] If desired, the compositions may also contain small amounts of wetting or emulsifying agents, or pH buffering agents. These compositions may take the form of solutions, suspensions, emulsions, tablets, pills, capsules, powders, sustained release formulations, and the like. Oral formulations may contain standard carriers, such as pharmaceutical grade mannitol, lactose, starch, magnesium stearate, sodium saccharin, cellulose, magnesium carbonate, and the like. Examples of suitable pharmaceutical carriers are described in "Remington's Pharmaceutical Sciences" by EW Martin. Such compositions will contain a prophylactically or therapeutically effective amount of the prophylactic or therapeutic agent, preferably in purified form, together with an amount of carrier suitable to provide the form for proper administration to a patient. The formulation will be suitable for the mode of administration. In some embodiments, the pharmaceutical composition is sterile and in a form suitable for administration to a subject, preferably an animal subject, more preferably a mammalian subject, and most preferably in a form suitable for administration to a human subject.

[0084] In some embodiments, it is desirable to administer the pharmaceutical composition locally to the area requiring treatment; this can be achieved, for example and without limitation, by local infusion, by injection, or by implants that are porous, non-porous, or gelatinous materials, including membranes such as Sialastic membranes or fibers.Preferably, when administering anti-CD3 antibodies, care must be taken to use materials to which the anti-CD3 antibodies do not adsorb.

[0085] In some embodiments, the compositions are delivered by vesicles, in particular liposomes (see Langer, Science, 249:1527-1533 (1990); Treat et al., "Liposomes," in Therapy of Infectious Disease and Cancer, Lopez-Berestein and Fidler (eds.), Liss, New York, 353-365 (1989); Lopez-Berestein, ibid., 317-327; see generally, ibid.).

[0086] In some embodiments, the composition is delivered by a controlled or sustained release system. In some embodiments, pumps are used to achieve controlled or sustained release (see Langer, supra; Sefton, 1987, CRC Crit. Ref. Biomed. Eng., 14:20; Buchwald et al., 1980, Surgery, 88:507; Saudek et al., 1989, N. Engl. J. Med., 321:574). In some embodiments, polymeric materials are used to achieve controlled or sustained release of the antibodies or fragments thereof of the invention (see, e.g., "Medical Applications of Controlled Release", Langer and Wise (eds.), CRC Pres., Boca Raton, Fla. (1974); "Controlled Drug Bioavailability", "Drug Product Design and Performance", Smolen and Ball (eds.), Wiley, New York, 1999). See York (1984); Ranger and Peppas, 1983, J. Macromol. Sci. Rev. Macromol. Chem., 23:61; see also Levy et al., 1985, Science, 228:190; During et al., 1989, Ann. Neurol. 25:351; Howard et al., 1989, J. Neurosurg. 71:105; U.S. Patent No. 5,679,377; U.S. Patent No. 5,916,597; U.S. Patent No. 5,912,015; U.S. Patent No. 5,989,463; U.S. Patent No. 5,128,326; PCT Publication No. WO 99 / 15154; and PCT Publication No. WO 99 / 20253). Examples of polymers used in sustained release formulations include, but are not limited to, poly(2-hydroxyethyl methacrylate), poly(methyl methacrylate), poly(acrylic acid), poly(ethylene-co-vinyl acetate), poly(methacrylic acid), polyglycolide (PLG), polyanhydrides, poly(N-vinylpyrrolidone), poly(vinyl alcohol), polyacrylamide, poly(ethylene glycol), polylactide (PLA), poly(lactide-co-glycolide) (PLGA), and polyorthoesters.In some embodiments, the polymers used in the sustained release formulations are inert, free of leachable impurities, stable on storage, sterile, and biodegradable. In some embodiments, the controlled or sustained release systems are placed in close proximity to a specific therapeutic target, i.e., the lungs, and thus require only a fraction of the systemic dose (see, e.g., Goodson, Medical Applications of Controlled Release, supra, vol. 2, pp. 115-138 (1984)).

[0087] Controlled release systems are discussed in the review by Langer (1990, Science, 249:1527-1533). Any technique known to those skilled in the art can be used to prepare sustained release formulations containing one or more of the antibodies or fragments thereof of the invention. See, e.g., U.S. Pat. No. 4,526,938, PCT Publication Nos. WO 91 / 05548, and WO 96 / 20698, Ning et al., 1996, Radiotherapy & Oncology, 39:179-89; Song et al., 1995, PDA J. of Pharma. Sci. & Tech., 50:372-397; Cleek et al., 1997, Pro. Int'l. Symp. Control Rel. Bioact. Mater., 24:853-54, and Lam et al., 1997, Proc. Int'l. Symp. Control Rel. Bioact. Mater., 24:759-760, each of which is incorporated herein by reference in its entirety.

[0088] A pharmaceutical composition is formulated to be compatible with its intended route of administration. Examples of routes of administration include parenteral administration, e.g., intravenous administration, intradermal administration, subcutaneous administration, oral administration, intranasal administration (e.g., inhalation), transdermal (topical) administration, transmucosal administration, and rectal administration. In some embodiments, the composition is formulated according to routine procedures as a pharmaceutical composition adapted for intravenous, subcutaneous, intramuscular, oral, intranasal, or topical administration to humans. In some embodiments, the pharmaceutical composition is formulated according to routine procedures for subcutaneous administration to humans. Typically, compositions for intravenous administration are solutions in sterile isotonic aqueous buffer. If necessary, the composition may also include a local anesthetic, such as lidocaine, to ease pain at the site of injection.

[0089] The composition is formulated for parenteral administration by injection, for example, bolus injection or continuous infusion.The preparation for injection is presented in unit dosage form, for example, in ampoules or multi-dose containers with added preservative.The composition may take the form of suspension, solution, or emulsion in oily or aqueous medium, and may contain formulating agents such as suspending, stabilizing, and / or dispersing agents.Alternatively, the active ingredient may be in powder form for constitution with suitable medium, for example, pyrogen-free water, before use.

[0090] In some embodiments, the present disclosure provides dosage forms that allow for continuous administration of anti-CD3 antibodies over a period of hours or days (e.g., in conjunction with a pump or other device for such delivery), e.g., 1 hour, 2 hours, 3 hours, 4 hours, 6 hours, 8 hours, 10 hours, 12 hours, 16 hours, 20 hours, 24 hours, 30 hours, 36 hours, 4 days, 5 days, 7 days, 10 days, or 14 days. In some embodiments, the present invention provides for continuous escalation of the dose, e.g., 51 ug / m2 over 24 hours, 30 hours, 36 hours, 4 days, 5 days, 7 days, 10 days, or 14 days. 2 / day to 826ug / m 2 The present invention provides a dosage form that allows for increased dosing per day.

[0091] The compositions are formulated as neutral or salt forms. Pharmaceutically acceptable salts include salts formed with anions such as those derived from hydrochloric acid, phosphoric acid, acetic acid, oxalic acid, tartaric acid, etc., and salts formed with cations such as those derived from sodium, potassium, ammonium, calcium, ferric hydroxide, isopropylamine, triethylamine, 2-ethylaminoethanol, histidine, procaine, etc.

[0092] In general, the components of the compositions disclosed herein are supplied individually or mixed together in unit dosage form, for example as lyophilized powders or water-free concentrates in a sealed container, such as an ampoule or sachet indicating the quantity of active agent. When the composition is administered by infusion, it is dispensed with an infusion bottle containing sterile pharmaceutical grade water or saline. When the composition is administered by injection, an ampoule of sterile water for injection or saline is provided so that the components can be mixed prior to administration.

[0093] In particular, the present disclosure provides that the anti-CD3 antibody or pharmaceutical composition thereof is packaged in a sealed container, such as an ampoule or sachet indicating the quantity of the agent. In some embodiments, the anti-CD3 antibody or pharmaceutical composition thereof is provided as a sterile lyophilized powder or water-free concentrate in a sealed container and reconstituted, for example, with water or saline, to a concentration suitable for administration to a subject. Preferably, the anti-CD3 antibody or pharmaceutical composition thereof is provided in a unit dose of at least 5 mg, more preferably at least 10 mg, at least 15 mg, at least 25 mg, at least 35 mg, at least 45 mg, at least 50 mg, at least 75 mg, or at least 100 mg as a sterile lyophilized powder or water-free concentrate in a sealed container. The lyophilized prophylactic or pharmaceutical composition herein is intended to be stored in its original container at between 2°C and 8°C, and the prophylactic or therapeutic agent or pharmaceutical composition of the present invention is intended to be administered within one week, preferably within 5 days, 72 hours, 48 ​​hours, 24 hours, 12 hours, 6 hours, 5 hours, 3 hours, or 1 hour after reconstitution. In some embodiments, the pharmaceutical composition is provided in liquid form in a sealed container indicating the quantity and concentration of the agent. Preferably, the liquid form of the composition to be administered is provided in a sealed container at at least 0.25 mg / ml, more preferably at least 0.5 mg / ml, at least 1 mg / ml, at least 2.5 mg / ml, at least 5 mg / ml, at least 8 mg / ml, at least 10 mg / ml, at least 15 mg / ml, at least 25 mg / ml, at least 50 mg / ml, at least 75 mg / ml, or at least 100 mg / ml. The liquid form is intended to be stored in its original container at between 2°C and 8°C.

[0094] In some embodiments, the disclosure provides that the compositions of the invention are packaged in a hermetically sealed container, such as an ampoule or sachet indicating the quantity of anti-CD3 antibody.

[0095] The compositions may, if desired, be presented in a pack or dispenser device which may contain one or more unit dosage forms containing the active ingredient. The pack may, for example, comprise metal or plastic foil, such as a blister pack.

[0096] The amount of the composition of the present invention that is effective in preventing or improving one or more symptoms associated with T1D can be determined by standard clinical methods.The exact dose to be incorporated in the formulation also depends on the route of administration and the severity of the condition, and should be determined according to the judgment of a medical professional and each patient's circumstances.Effective doses can be extrapolated from dose-response curves from in vitro or animal model test systems.

[0097] Methods and Uses The methods disclosed herein are used for prognosis of any therapeutic or prophylactic agent in the treatment or prevention of any stage of T1D, including stages 1, 2, 3, or 4. In some embodiments, the disclosure encompasses administration of an anti-human CD3 antibody, such as teplizumab, to individuals who are predisposed to developing type 1 diabetes or who are involved in the preclinical stage of type 1 diabetes, but who do not meet the diagnostic criteria established by the American Diabetes Association or the Immunology of Diabetes Society to prevent or delay the onset of type 1 diabetes and / or prevent or delay the need for administration of exogenous insulin to such patients.

[0098] In some embodiments, new metabolic endpoints are used to detect the effect of drugs on the treatment or prevention of T1D after administration. GCRC (glucose and C-peptide response curve) is constructed by plotting the mean blood glucose value and the mean C-peptide value by oral glucose tolerance test on a two-dimensional grid. The shape and movement changes of GCRC are visually compared between placebo group and treatment group. If the change of GCRC in placebo group reflects significant metabolic deterioration, while the change of GCRC in treatment group suggests metabolic improvement, the drug is effective in the treatment or prevention of T1D. Quantitative comparison is also used, including two new metabolic endpoints that indicate GCRC change, WQE (Within Quadrant Endpoint) and ODE (Ordinal Directional Endpoint).

[0099] In some embodiments, the Within Quadrant Endpoint (WQE) is used. Specifically, prediction or prognosis of T1D risk is enhanced by dividing the 360° continuum into its four directional quadrants, ranging from 0° to 90°. Each directional quadrant is believed to represent its own characteristic risk, which, when combined together in the model, may predict overall risk. The directional quadrants are: Upper Right Quadrant (RUQ) Upper Left Quadrant (LUQ) Lower Right Quadrant (RLQ) Lower left quadrant (LLQ) is specified as

[0100] Angles are calculated from a right triangle formed according to the directional quadrants of each change vector. Negative calculated angles are converted to positive calculated angles. The percent change in glycemic centroid from baseline to 6 months on the y-axis and the percent change in C-peptide centroid from baseline to 6 months on the x-axis are used to calculate the angle. The hypotenuse of the triangle represents the distance from the GCRC centroid at baseline to the GCRC centroid at 6 months (i.e., the vector magnitude of the change). The formulas for the calculated angle and hypotenuse are shown below: radian = arctangent (% change in blood glucose / % change in C-peptide) Degrees = Radians x 57.296 Hypotenuse = Square root of ((% change in blood glucose × % change in blood glucose) + (% change in C-peptide × % change in C-peptide)) (The formula uses percent changes in blood glucose and C-peptide instead of actual measurements to normalize the units of the sides of the triangle).

[0101] A Cox regression model is developed that incorporates the calculated angle of change over 6 months within each quadrant as an independent variable for predicting type 1 diabetes. Since each change vector falls within only one of the quadrants, the values ​​in the other quadrants are assigned a value of 0. Based on this paradigm, the model is shown to significantly predict type 1 diabetes. However, if the calculated angle for a particular quadrant is subtracted from 90°, other models are also predictive.

[0102] The formula below shows the coefficient of orientation quadrant angle used for the exemplary model to detect the maximum difference between the oral insulin group and the placebo group (p<0.001). WQE=0.02455×qangle1+0.01464×qangle2+0.00831×qangle3-0.00465×qangle4 [Let qangle1=RUQ, qangle2=LUQ, qangle3=LLQ, and qangle4=RLQ] (for an individual, three of the four orientation quadrants will always be negative, so we used an indicator variable coded as "0").

[0103] The following outline shows the steps for calculating WQE: Calculation of blood glucose / C-peptide coordinates for the GCRC centroid at baseline and 6 months. Conversion of change in blood glucose / C-peptide centroid coordinates to percent change. Identify the directional quadrant for the vector between the baseline coordinate and the 6-month coordinate. · Calculate the angle between a horizontal line and a vector in a quadrant using the standard formula based on a right triangle. · Convert negative angles in direction quadrants 2 and 4 (qangle2 and qangle4) to positive angles. For qangle1 and qangle2, use the calculated angle. In the model, use (90° - calculated angle) for qangle3 and (90 - qangle4).

[0104] The procedure for converting angles from negative to positive, and subtracting angles from 90°, is given below: If the vector for the change in center of gravity is within RUQ, then qangle1 = the calculated angle. If the vector for the change in center of gravity is in LUQ, then qangle2 = calculated angle x (-1). If the vector for the change in center of gravity is within the LLQ, then qangle3 = 90 - the calculated angle. If the vector for the change in center of gravity is within the LLQ, then qangle4=90-calculated angle x (-1).

[0105] In some embodiments, an Ordinal Directional Endpoint (ODE) may be used. Using a 360° scale, values ​​are assigned to four quadrants according to historical evidence of directionality at any given time in the progression towards type 1 diabetes over time, as indicated below: Lower Right Quadrant (RLQ): 0° Lower left quadrant (LLQ): 90° Upper Right Quadrant (RUQ): 180° Upper Left Quadrant (LUQ): 270°

[0106] The value can be added to the value of qangle obtained from the WQE model. The sum is then divided by 360 to create a scale with a maximum of 1.00.

[0107] The process outline for computing the ODE can be the same as the process outline for computing the WQE, except that instead of inserting the qangle value into the model, the qangle is added to the specified value indicated above for the direction quadrant.

[0108] In some embodiments, high risk factors for identification of a predisposed subject include having a first or second degree relative diagnosed with type 1 diabetes, impaired fasting glucose (e.g., at least one determination of a blood glucose level of 100-125 mg / dl after fasting (after 8 hours without food)), impaired glucose tolerance in response to a 75 g OGTT (e.g., at least one determination of a blood glucose level of 140-199 mg / dl after 2 hours in response to a 75 g OGTT), HbA1c between 5.7-6.4%, or a 10% or greater increase in HbA1c compared to HbA1c values ​​over the past 12 months, white blood cells, or the like. These include HLA types of DR3, DR4, or DR7 in people of color, HLA types of DR3 or DR4 in people of African descent, HLA types of DR3, DR4, or DR9 in people of Japanese descent, exposure to a virus (e.g., Coxsackievirus type B, enterovirus, adenovirus, rubella virus, cytomegalovirus, Epstein-Barr virus), a positive diagnosis of at least one other autoimmune disorder (e.g., thyroid disease, celiac disease) according to art-accepted criteria, and / or detection of autoantibodies, particularly ICA and type 1 diabetes-related autoantibodies, in serum or other tissues. In some embodiments, subjects identified as having a predisposition to developing type 1 diabetes have at least one of the risk factors described herein and / or known in the art. The present disclosure also encompasses the identification of subjects predisposed to developing type 1 diabetes, where the subject presents a combination of two or more, three or more, four or more, or more than five risk factors disclosed herein or known in the art.

[0109] Serum autoantibodies associated with type 1 diabetes or a predisposition to developing type 1 diabetes are pancreatic islet cell autoantibodies (e.g., anti-ICA512 autoantibodies), glutamic acid decarbamylase autoantibodies (e.g., anti-GAD65 autoantibodies), IA2 antibodies, ZnT8 antibodies, and / or anti-insulin autoantibodies. Thus, in a specific example according to this embodiment, the invention encompasses the treatment of an individual with detectable autoantibodies (e.g., anti-IA2, anti-ICA512, anti-GAD or anti-insulin autoantibodies) associated with a predisposition to developing type 1 diabetes or associated with early stage type 1 diabetes, where the individual has not been diagnosed with type 1 diabetes and / or is a first or second degree relative of a type 1 diabetic individual. In some embodiments, the presence of autoantibodies is detected by ELISA, electrochemiluminescence (ECL), radioassay (see, e.g., Yu et al., 1996, J. Clin. Endocrinol. Metab., 81:4264-4267), agglutination PCR (Tsai et al., ACS Central Science, 20162(3), 139-147), or any other method for immunospecific detection of antibodies described herein or known to one of skill in the art.

[0110] Beta cell function before, during, and after treatment can be evaluated by any method described herein or known to those skilled in the art. For example, the Diabetes Control and Complications Trial (DCCT) research group has established the monitoring of percentage glycosylated hemoglobin (HA1 and HA1c) as the standard method for assessing glycemic control (DCCT, 1993, N. Engl. J. Med., 329:977-986). Alternatively, daily insulin requirements, C-peptide levels / response, hypoglycemic interval, and / or FPIR are also used as markers of beta cell function or to establish a therapeutic index (see, respectively, Keymeulen et al., 2005, N. Engl. J. Med., 352:2598-2608; Herold et al., 2005, Diabetes, 54:1763-1769; U.S. Patent Application Publication No. 2004 / 0038867 A1; and Greenbaum et al., 2001, Diabetes, 50:470-476). For example, FPIR is calculated as the sum of insulin values ​​at 1 and 3 minutes after an IGTT performed according to the Islet Cell Antibody Register User's Study protocols (see, e.g., Bingley et al., 1996, Diabetes, 45:1720-1728; and McCulloch et al., 1993, Diabetes Care, 16:911-915).

[0111] In some embodiments, an individual predisposed to developing T1D may be a non-clinically diabetic subject who is a relative of a patient with T1D. In some embodiments, the non-clinically diabetic subject has two or more diabetes-associated autoantibodies selected from islet cytoplasmic antibodies (ICA), insulin autoantibodies (IAA), and antibodies against glutamic acid decarboxylase (GAD), tyrosine phosphatase (IA-2 / ICA512), or ZnT8.

[0112] In some embodiments, the non-clinically diabetic subject has impaired glucose tolerance in an oral glucose tolerance test (OGTT), defined as a fasting glucose level of 110-125 mg / dL, or a 2-hour glucose level of ≧140 and <200 mg / dL, or a random glucose level of >200 mg / dL at 30, 60, or 90 minutes after the OGTT.

[0113] In some embodiments, non-clinically diabetic subjects who respond to anti-CD3 antibodies such as teplizumab are negative for ZnT8 antibodies. In some embodiments, such non-clinically diabetic subjects are HLA-DR4+. In some embodiments, such non-clinically diabetic subjects are not HLA-DR3+. In some embodiments, such non-clinically diabetic subjects are HLA-DR4+ and not HLA-DR3+. In some embodiments, such non-diabetic subjects are negative for antibodies to ZnT8, and are HLA-DR4+ and not HLA-DR3+. In some embodiments, such non-clinically diabetic subjects who respond to anti-CD3 antibodies such as teplizumab demonstrate an increase in the frequency (or relative amount) of TIGIT+KLRG1+CD8+ T cells in peripheral blood mononuclear cells (e.g., by flow cytometry) after administration (e.g., 1 month, 2 months, 3 months or more or earlier).

[0114] In some embodiments, a prophylactically effective amount is between 10 and 1100 micrograms per square meter (μg / m 2 ) in a 10-14 day course of subcutaneous (SC) injection or intravenous (IV) infusion of an anti-CD3 antibody, such as teplizumab. In one example, a prophylactically effective dose is 51 μg / m on days 1-4, respectively. 2 , 103 μg / m 2 , 207 μg / m 2 , and 413 μg / m 2 , and 826 μg / m on each of days 5 to 14. 2by IV infusion of an anti-CD3 antibody, such as teplizumab, at a single dose of 0.1 mg / kg / day. In some embodiments, the prophylactically effective amount delays the median time to clinical diagnosis of T1D by at least 50%, at least 80%, or at least 90%, about 50% to about 90%. In some embodiments, the prophylactically effective amount delays the median time to clinical diagnosis of T1D by at least 12 months, at least 18 months, at least 24 months, at least 36 months, at least 48 months, or at least 60 months or more, or by about 12 months to about 28 months, about 12 months to about 24 months, about 12 months to about 36 months, about 12 months to about 48 months, about 12 months to about 60 months or more.

[0115] In some embodiments, the course of administration with an anti-CD3 antibody, such as teplizumab, is repeated at intervals of 2 months, 4 months, 6 months, 8 months, 9 months, 10 months, 12 months, 15 months, 18 months, 24 months, 30 months, or 36 months. In some embodiments, the efficacy of treatment with an anti-CD3 antibody, such as teplizumab, is determined 2 months, 4 months, 6 months, 9 months, 12 months, 15 months, 18 months, 24 months, 30 months, or 36 months following the previous treatment, as described herein or known in the art.

[0116] In some embodiments, a subject is administered one or more unit doses of an anti-CD3 antibody, such as teplizumab, that is about 0.5-50ug / kg, about 0.5-40ug / kg, about 0.5-30ug / kg, about 0.5-20ug / kg, about 0.5-15ug / kg, about 0.5-10ug / kg, about 0.5-5ug / kg, about 1-5ug / kg, about 1-10ug / kg, about 20-40ug / kg, about 20-30ug / kg, about 22-28ug / kg, or about 25-26ug / kg to prevent, treat, or ameliorate one or more symptoms of T1D. In some embodiments, the subject is administered about 200ug / kg, 178ug / kg, 180ug / kg, 128ug / kg, 100ug / kg, 95ug / kg, 90ug / kg, 85ug / kg, 80ug / kg, 75ug / kg, 70ug / kg, 65ug / kg, 60ug / kg, 55ug / kg, 50ug / kg, 45ug / kg, 40ug / kg, 35ug / kg, 30ug / kg, 40ug / kg, 45 ...5ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, 45ug / kg, In one or more doses, the patient is administered an anti-CD3 antibody, such as teplizumab, in a unit dose of 1.6ug / kg, 1.5ug / kg, 1ug / kg, 0.5ug / kg, 0.25ug / kg, 0.1ug / kg, or 0.05ug / kg.

[0117] In some embodiments, the subject receives a dose of about 5-1200 ug / m 2 , e.g., 51-826ug / m 2 In some embodiments, subjects receive one or more doses of an anti-CD3 antibody, such as teplizumab, in an amount of 1200 ug / m to prevent, treat, slow the progression of, delay the onset of, or ameliorate one or more symptoms of T1D. 2 , 1150ug / m 2 , 1100ug / m 2 , 1050ug / m 2, 1000ug / m 2 , 950ug / m 2 , 900ug / m 2 , 850ug / m 2 , 800ug / m 2 , 750ug / m 2 , 700ug / m 2 , 650ug / m 2 , 600ug / m 2 , 550ug / m 2 , 500ug / m 2 , 450ug / m 2 , 400ug / m 2 , 350ug / m 2 , 300ug / m 2 , 250ug / m 2 , 200ug / m 2 , 150ug / m 2 , 100ug / m 2 , 50ug / m 2 , 40ug / m 2 , 30ug / m 2 , 20ug / m 2 , 15ug / m 2 , 10ug / m 2 , or 5ug / m 2 The patient is administered one or more unit doses of an anti-CD3 antibody, such as teplizumab,

[0118] In some embodiments, the subject is administered a treatment regimen comprising one or more administrations of a prophylactically effective amount of an anti-CD3 antibody, such as teplizumab, and the treatment course is administered for 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days. In some embodiments, the treatment regimen comprises administering a prophylactically effective amount of a dose every day, every other day, every 3rd day, or every 4th day. In some embodiments, the treatment regimen comprises administering a prophylactically effective amount of a dose on Monday, Tuesday, Wednesday, and Thursday of a given week, and not administering a prophylactically effective amount of a dose on Friday, Saturday, and Sunday of the same week, until 14 doses, 13 doses, 12 doses, 11 doses, 10 doses, 9 doses, or 8 doses have been administered. In some embodiments, the doses administered are the same doses on each day of the regimen.

[0119] In some embodiments, a subject is administered a treatment regimen comprising one or more administrations of a prophylactically effective amount of an anti-CD3 antibody, such as teplizumab, where the prophylactically effective amount is 200ug / kg / day, 175ug / kg / day, 150ug / kg / day, 125ug / kg / day, 100ug / kg / day, 95ug / kg / day, 90ug / kg / day, 85ug / kg / day, 80ug / kg / day, 75ug / kg / day, 70ug / kg / day, 65ug / kg / day, 60ug / kg / day, 55ug / kg / day, 50ug / kg / day, 45ug / kg / day, 40ug / kg / day, kg / day, 35ug / kg / day, 30ug / kg / day, 26ug / kg / day, 25ug / kg / day, 20ug / kg / day, 15ug / kg / day, 13ug / kg / day, 10ug / kg / day, 6.5ug / kg / day, 5ug / kg / day, 3.2ug / kg / day, 3ug / kg / day, 2.5ug / kg / day, 2ug / kg / day, 1.6ug / kg / day, 1.5ug / kg / day, 1ug / kg / day, 0.5ug / kg / day, 0.25ug / kg / day, 0.1ug / kg / day, or 0.05ug / kg / day; and / or the prophylactically effective amount is 1200ug / m 2 / day, 1150ug, 1100ug / m 2 / day, 1050ug / m 2 / day, 1000ug / m 2 / day, 950ug / m 2 / day, 900ug / m 2 / day, 850ug / m 2 / day, 800ug / m 2 / day, 750ug / m 2 / day, 700ug / m 2 / day, 650ug / m 2 / day, 600ug / m 2 / day, 550ug / m 2 / day, 500ug / m 2 / day, 450ug / m 2 / day, 400ug / m 2 / day, 350ug / m 2 / day, 300ug / m 2 / day, 250ug / m 2 / day, 200ug / m 2 / day, 150ug / m 2 / day, 100ug / m 2 / day, 50ug / m 2 / day, 40ug / m 2 / day, 30ug / m 2 / day, 20ug / m 2 / day, 15ug / m 2 / day, 10ug / m 2 / day, or 5ug / m 2 / day.

[0120] In some embodiments, 1200 ug / m 2 or less, 1150ug / m 2 or less, 1100ug / m 2 or less, 1050ug / m 2 or less, 1000ug / m 2 or less, 950ug / m 2 Or less, 900ug / m 2 or less, 850ug / m 2 Or less, 800ug / m 2 or less, 750ug / m 2 Or less, 700ug / m 2 or less, 650ug / m 2or less, 600ug / m 2 or less, 550ug / m 2 Or less, 500ug / m 2 or less, 450ug / m 2 Or less, 400ug / m 2 or less, 350ug / m 2 Or less, 300ug / m 2 or less, 250ug / m 2 Or less, 200ug / m 2 or less, 150ug / m 2 or less, 100ug / m 2 or less, 50ug / m 2 or less, 40ug / m 2 or less, 30ug / m 2 or less, 20ug / m 2 or less, 15ug / m 2 or less, 10ug / m 2 or less, or 5ug / m 2 A dose of intravenous administration of an anti-CD3 antibody, such as teplizumab, that is greater than or equal to about 24 hours, about 22 hours, about 20 hours, about 18 hours, about 16 hours, about 14 hours, about 12 hours, about 10 hours, about 8 hours, about 6 hours, about 4 hours, about 2 hours, about 1.5 hours, about 1 hour, about 50 minutes, about 40 minutes, about 30 minutes, about 20 minutes, about 10 minutes, about 5 minutes, about 2 minutes, about 1 minute, about 30 seconds, or about 10 seconds is administered to prevent, treat, or ameliorate one or more symptoms of type 1 diabetes. In some embodiments, the total dose administered over the duration of the regimen is greater than or equal to 9000 ug / m 2 , 8000ug / m 2 , 7000ug / m 2 , 6000ug / m 2 Less than 5000ug / m 2 , 4000ug / m 2 , 3000ug / m 2 , 2000ug / m 2 , or 1000ug / m 2In some embodiments, the total dose administered over the duration of the regimen may be less than 9000 ug / m 2 , for example, about 9000ug / m 2 ~About 14000ug / m 2 In some embodiments, the total dose administered during the regimen is greater than 100 ug / m 2 ~200ug / m 2 , 100ug / m 2 ~500ug / m 2 , 100ug / m 2 ~1000ug / m 2 , or 500ug / m 2 ~1100ug / m 2 It is.

[0121] In some embodiments, the dose is escalated over the first quarter, half, or two-thirds of the dose of the treatment regimen (e.g., over the first 2, 3, 4, 5, or 6 days of a 10, 12, 14, 16, 18, or 20 day regimen with one administration per day) until a prophylactically effective daily amount of an anti-CD3 antibody, such as teplizumab, is achieved. In some embodiments, a subject is administered a treatment regimen that includes one or more administrations of a prophylactically effective amount of an anti-CD3 antibody, such as teplizumab, where the prophylactically effective amount is, for example, 0.01 ug / kg, 0.02 ug / kg, 0.04 ug / kg, 0.05 ug / kg, 0.06 ug / kg, 0.08 ug / kg, 0.1 ug / kg, 0.2 ug / kg, 0.25 ug / kg, 0.5 ug / kg, 0.75 ug / kg, 1 ug / kg, 1.5 ug / kg, 2 ug / kg, 3 ug / kg, 4 ug / kg, 5 ug / kg, 6 ug / kg, 7 ug / kg, 8 ug / kg, 9 ug / kg, 10 ug / kg, 11 ug / kg, 12 ug / kg, 13 ug / kg, 14 ug / kg, 15 ug / kg, 16 ug / kg, 17 ug / kg, 18 ug / kg, 19 ug / kg, 20 ug / kg, 21 ug / kg, 22 ug / kg, 23 ug / kg, 24 ug / kg, 25 ug / kg, 26 ug / kg, 27 ug / kg, 28 ug / kg, 29 ug / kg, 30 ug / kg, 31 ug / kg, 32 ug / kg, 33 ug / kg, 34 ug / kg, 35 ug / kg, 36 ug / kg, 37 ug / kg, 38 ug / kg, 39 ug / kg, 40 ug / kg, 41 ug / kg, 42 ug / kg, 43 ug / kg, 44 g, 4ug / kg, 5ug / kg, 10ug / kg, 15ug / kg, 20ug / kg, 25ug / kg, 30ug / kg, 35ug / kg, 40ug / kg, 45ug / kg, 50ug / kg, 55ug / kg, 60ug / kg, 65ug / kg, 70ug / kg, 75ug / kg, 80ug / kg, 85ug / kg, 90ug / kg, 95ug / kg, 100ug / kg, or 125ug / kg; or increased by, for example, 1ug / m each day as treatment progresses. 2 , 5ug / m 2 , 10ug / m2 , 15ug / m 2 , 20ug / m 2 , 30ug / m 2 , 40ug / m 2 , 50ug / m 2 , 60ug / m 2 , 70ug / m 2 , 80ug / m 2 , 90ug / m 2 , 100ug / m 2 , 150ug / m 2 , 200ug / m 2 , 250ug / m 2 , 300ug / m 2 , 350ug / m 2 , 400ug / m 2 , 450ug / m 2 , 500ug / m 2 , 550ug / m 2 , 600ug / m 2 , or 650ug / m 2 In some embodiments, a subject is administered a treatment regimen comprising one or more administrations of a prophylactically effective amount of an anti-CD3 antibody, such as teplizumab, where the prophylactically effective amount is increased by 1.25-fold, 1.5-fold, 2-fold, 2.25-fold, 2.5-fold, or 5-fold until a daily prophylactically effective amount of an anti-CD3 antibody, such as teplizumab, is achieved.

[0122] In some embodiments, the subject is administered 200ug / kg or less, preferably 175ug / kg or less, 150ug / kg or less, 125ug / kg or less, 100ug / kg or less, 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, or less than 100ug / kg to prevent, treat, or ameliorate one or more symptoms of T1D. An anti-CD3 antibody such as teplizumab, otelixizumab, or foralumab is administered intramuscularly in one or more doses of 1.5 ug / kg or less, 40 ug / kg or less, 35 ug / kg or less, 30 ug / kg or less, 25 ug / kg or less, 20 ug / kg or less, 15 ug / kg or less, 10 ug / kg or less, 5 ug / kg or less, 2.5 ug / kg or less, 2 ug / kg or less, 1.5 ug / kg or less, 1 ug / kg or less, 0.5 ug / kg or less, or 0.2 ug / kg or less.

[0123] In some embodiments, the subject is administered 200ug / kg or less, preferably 175ug / kg or less, 150ug / kg or less, 125ug / kg or less, 100ug / kg or less, 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, or less than 100ug / kg to prevent, treat, or ameliorate one or more symptoms of T1D. The anti-CD3 antibody, such as teplizumab, otelixizumab, or foralumab, is administered subcutaneously in one or more doses of ug / kg or less, 40ug / kg or less, 35ug / kg or less, 30ug / kg or less, 25ug / kg or less, 20ug / kg or less, 15ug / kg or less, 10ug / kg or less, 5ug / kg or less, 2.5ug / kg or less, 2ug / kg or less, 1.5ug / kg or less, 1ug / kg or less, 0.5ug / kg or less, or 0.2ug / kg or less.

[0124] In some embodiments, the subject is administered 100ug / kg or less, preferably 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, 40ug / kg or less, 35ug / kg or less, or less than 100ug / kg ... to prevent, treat, or ameliorate one or more symptoms of T1D. The patient is administered an anti-CD3 antibody such as teplizumab, otelixizumab, or foralumab intravenously in one or more doses of 10 ug / kg or less, 30 ug / kg or less, 25 ug / kg or less, 20 ug / kg or less, 15 ug / kg or less, 10 ug / kg or less, 5 ug / kg or less, 2.5 ug / kg or less, 2 ug / kg or less, 1.5 ug / kg or less, 1 ug / kg or less, 0.5 ug / kg or less, or 0.2 ug / kg or less.In some embodiments, the dose is 100ug / kg or less, 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, 40ug / kg or less, 35ug / kg or less, 30ug / kg or less, 25ug / kg or less, 20ug / kg or less, 15ug / kg or less, 10ug / kg or less. An intravenous dose of an anti-CD3 antibody, such as teplizumab, otelixizumab, or foralumab, of 5 ug / kg or less, 2.5 ug / kg or less, 2 ug / kg or less, 1.5 ug / kg or less, 1 ug / kg or less, 0.5 ug / kg or less, or 0.2 ug / kg or less is administered over about 6 hours, about 4 hours, about 2 hours, about 1.5 hours, about 1 hour, about 50 minutes, about 40 minutes, about 30 minutes, about 20 minutes, about 10 minutes, about 5 minutes, about 2 minutes, about 1 minute, about 30 seconds, or about 10 seconds to prevent, treat, or ameliorate one or more symptoms of T1D.

[0125] In some embodiments, the subject is administered 100ug / kg or less, preferably 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, 40ug / kg or less, 35ug / kg or less, or less than 100ug / kg ... to prevent, treat, or ameliorate one or more symptoms of T1D. In some embodiments, the patient is orally administered an anti-CD3 antibody such as teplizumab, otelixizumab, or foralumab in one or more doses of 10 ug / kg or less, 30 ug / kg or less, 25 ug / kg or less, 20 ug / kg or less, 15 ug / kg or less, 10 ug / kg or less, 5 ug / kg or less, 2.5 ug / kg or less, 2 ug / kg or less, 1.5 ug / kg or less, 1 ug / kg or less, 0.5 ug / kg or less, or 0.2 ug / kg or less.In some embodiments, the dose is 100ug / kg or less, 95ug / kg or less, 90ug / kg or less, 85ug / kg or less, 80ug / kg or less, 75ug / kg or less, 70ug / kg or less, 65ug / kg or less, 60ug / kg or less, 55ug / kg or less, 50ug / kg or less, 45ug / kg or less, 40ug / kg or less, 35ug / kg or less, 30ug / kg or less, 25ug / kg or less, 20ug / kg or less, 15ug / kg or less, 10ug / kg or less. Orally administered doses of anti-CD3 antibodies, such as teplizumab, otelixizumab, or foralumab, of 5 ug / kg or less, 2.5 ug / kg or less, 2 ug / kg or less, 1.5 ug / kg or less, 1 ug / kg or less, 0.5 ug / kg or less, or 0.2 ug / kg or less, are administered over about 6 hours, about 4 hours, about 2 hours, about 1.5 hours, about 1 hour, about 50 minutes, about 40 minutes, about 30 minutes, about 20 minutes, about 10 minutes, about 5 minutes, about 2 minutes, about 1 minute, about 30 seconds, or about 10 seconds to prevent, treat, or ameliorate one or more symptoms of T1D.

[0126] Increasing doses are administered over the first few days of the dosing regimen. In some embodiments, the dose on day 1 of the regimen is 5-100 ug / m 2 / day, e.g., 51ug / m 2 / day, titrating to the daily doses listed immediately above by days 3, 4, 5, 6, or 7. For example, a subject may receive about 51 ug / m 2 / day dose, approximately 103ug / m on day 2 2 / day dose, approximately 207ug / m on day 3 2 / day dose, approximately 413ug / m on day 4 2 / day and 826ug / m on subsequent days of the regimen (e.g., days 5-14). 2In some embodiments, subjects receive a dose of about 227 ug / m on day 1. 2 / day dose, approximately 459ug / m on day 2 2 / day dose, approximately 919ug / m after the 3rd day 2 In some embodiments, subjects receive a dose of about 284 ug / m on day 1. 2 / day dose, approximately 574ug / m on day 2 2 / day dose, approximately 1148ug / m after day 3 2 / day.

[0127] In some embodiments, the initial dose is a quarter to a half or even equal to the daily dose at the end of the regimen, but is administered in several doses at 6, 8, 10, or 12 hour intervals. For example, a dose of 13ug / kg / day is administered four times at 3-4ug / kg, 6 hour intervals apart, to reduce the level of cytokine release caused by the administration of the antibody. In some embodiments, the first 1, 2, 3, or 4 doses or the entire dose of the regimen are administered more slowly by intravenous administration to reduce the possibility of cytokine release and other adverse effects. For example, a dose of 51ug / m 2 The daily dose is administered over about 5 minutes, about 15 minutes, about 30 minutes, about 45 minutes, about 1 hour, about 2 hours, about 4 hours, about 6 hours, about 8 hours, about 10 hours, about 12 hours, about 14 hours, about 16 hours, about 18 hours, about 20 hours, and about 22 hours. In some embodiments, the dose is administered over a 20-24 hour period by slowing the infusion. In some embodiments, the dose is administered by a pump, preferably increasing the concentration of the antibody administered as the infusion proceeds.

[0128] In some embodiments, the set of aliquot doses described above is 51 ug / m 2 / day~826ug / m 2The regimen is administered in escalating doses. In some embodiments, the split dose is one tenth, one quarter, one third, one half, two thirds, or three quarters of the daily dose of the regimen described above. Thus, when the split dose is one tenth, the daily dose is 5.1 ug / m on day 1, 5.2 ug / m on day 2, 5.3 ug / m on day 3, 5.4 ug / m on day 4, 5.5 ug / m on day 5, 5.6 ug / m on day 6, 5.7 ug / m on day 7, 5.8 ug / m on day 8, 5.9 ug / m on day 9, 5.8 ug / m on day 10, 5.9 ug / m on day 11, 5.9 ug / m on day 12, 5.9 ug / m on day 13, 5.9 ug / m on day 14, 2 , 10.3ug / m on the second day 2 , 20.7ug / m on the third day 2 , 41.3ug / m on the fourth day 2 , and 82.6ug / m on days 5–14. 2 If the dose is divided into 4 parts, the dose is 12.75ug / m on day 1. 2 , 25.5ug / m on the second day 2 , 51ug / m on the third day 2 , 103ug / m on the fourth day 2 , and 207ug / m on days 5–14. 2 If the dose is divided into thirds, the dose is 17ug / m on day 1. 2 , 34.3ug / m on the second day 2 , 69ug / m on the third day 2 , 137.6ug / m on the fourth day 2 , and 275.3ug / m on days 5–14. 2 If the dose is split in half, the dose is 25.5ug / m on day 1. 2 , 51ug / m on the second day 2 , 103ug / m on the third day 2 , 207ug / m on the fourth day 2 , and 413ug / m on days 5–14. 2 If the dose is split into two thirds, the dose is 34 ug / m on day 1. 2 , 69ug / m on the second day 2 , 137.6ug / m on the third day 2 , 275.3ug / m on the fourth day 2 , and 550.1ug / m on days 5–14. 2 If the dose is divided into three quarters, the dose is 38.3 ug / m on day 1. 2 , 77.3ug / m on the second day 2 , 155.3ug / m on the third day 2 , 309.8ug / m on the fourth day 2, and 620ug / m on days 5-14. 2 In some embodiments, the regimen is the same as one of the regimens described above, but only for days 1-4, days 1-5, or days 1-6. For example, in some embodiments, the dose is 17 ug / m on day 1, 17 ug / m on day 2, 17 ug / m on day 3, 17 ug / m on day 4, 17 ug / m on day 5, or 17 ug / m on day 6. 2 , 34.3ug / m on the second day 2 , 69ug / m on the third day 2 , 137.6ug / m on the fourth day 2 , and 275.3ug / m on days 5 and 6 2 It becomes.

[0129] In some embodiments, the anti-CD3 antibody, such as teplizumab, otelixizumab, or foralumab, is not administered over multiple days by daily dosing, but by continuous infusion over 4, 6, 8, 10, 12, 15, 18, 20, 24, 30, or 36 hours. The infusion may be constant, for example, starting at a low dose for the first 1, 2, 3, 5, 6, or 8 hours of the infusion, and then increasing to a higher dose thereafter. Over the course of the infusion, the patient is administered a dose equivalent to that administered in the 5-20 day regimen specified above. For example, about 150 ug / m 2 , 200ug / m 2 , 250ug / m 2 , 500ug / m 2 , 750ug / m 2 , 1000ug / m 2 , 1500ug / m 2 , 2000ug / m 2 , 3000ug / m 2 , 4000ug / m 2 , 5000ug / m 2 , 6000ug / m 2 , 7000ug / m 2 , 8000ug / m 2 , 9000ug / m 2 , 10000ug / m 2 , 11000ug / m 2 , 12000ug / m 2 , 13000ug / m 2, or 14000ug / m 2 In particular, the rate and duration of the infusion is designed to minimize the level of free anti-CD3 antibodies, such as teplizumab, otelixizumab, or foralumab, in the subject after administration. In some embodiments, the level of free anti-CD3 antibodies, such as teplizumab, does not exceed 200 ng of free antibody per ml. In addition, the infusion is designed to achieve a combination of coating and modulation by at least 50%, 60%, 70%, 80%, 90%, 95%, or 100% of T cell receptors.

[0130] In some embodiments, an anti-CD3 antibody, such as teplizumab, otelixizumab, or foralumab, is administered chronically to treat, prevent, or slow or delay the onset or progression of, or ameliorate one or more symptoms of, type 1 diabetes. For example, in some embodiments, a low dose of an anti-CD3 antibody, such as teplizumab, is administered monthly, twice monthly, three times monthly, weekly, or even more frequently following administration of the 6-14 day dosing regimen discussed above, or to enhance or maintain the effect of such a regimen. Such a low dose may be about 5ug / m 2 , 10ug / m 2 , 15ug / m 2 , 20ug / m 2 , 25ug / m 2 , 30ug / m 2 , 35ug / m 2 , 40ug / m 2 , 45ug / m 2 , or 50ug / m 2 etc., 1ug / m 2 ~100ug / m 2 It can be either of the following.

[0131] In some embodiments, a subject may be re-administered at a time subsequent to administration of a dosing regimen of an anti-CD3 antibody, such as teplizumab, otelixizumab, or foralumab, based on, for example, one or more physiological parameters, or may be re-administered as a course. Such re-administration may occur 2 months, 4 months, 6 months, 8 months, 9 months, 1 year, 15 months, 18 months, 2 years, 30 months, or 3 years after administration of the dosing regimen, and / or the need for such re-administration may be assessed at these time points, and may include administration of a course of treatment every 6 months, 9 months, 1 year, 15 months, 18 months, 2 years, 30 months, or 3 years indefinitely. EXAMPLES

[0132] Example 1 Prevention of rapid metabolic decline within 3 months of teplizumab treatment in individuals at high risk for type 1 diabetes Abstract To conduct type 1 diabetes prevention trials more efficiently, endpoints that provide early identification of treatment effects are needed. To this end, we evaluated whether metabolic endpoints could be used to detect the effect of teplizumab on rapid beta cell attenuation within 3 months of treatment in high-risk individuals in the TrialNet teplizumab trial. GCRCs (glucose and C-peptide response curves) were constructed by plotting mean blood glucose and C-peptide values ​​from a 2-hour oral glucose tolerance test on a 2-dimensional grid. Groups were compared visually for changes in GCRC shape and movement. In the placebo group, within 3 months of randomization, GCRC changes reflected significant metabolic deterioration. By 6 months, GCRCs closely resembled typical GCRCs at the time of diagnosis. In contrast, GCRC changes in the teplizumab group suggested metabolic improvement. Quantitative comparisons including two novel metabolic endpoints, the Within Quadrant Endpoint (WQE) and the Ordinal Directional Endpoint (ODE), indicative of GCRC changes, were consistent with the visual impression of a striking treatment effect at 3 and 6 months.In conclusion, analyses combining visual evidence with novel endpoints confirmed that teplizumab delayed the rapid metabolic decline and improved metabolic status within 3 months of treatment; this effect persisted for at least 6 months.

[0133] Introduction Type 1 diabetes is an autoimmune disease that results in insulin deficiency due to the destruction of pancreatic beta cells (1). In the Type 1 Diabetes TrialNet TN10 Anti-CD3 prevention study, a single 14-day course of teplizumab, a non-Fc receptor binding anti-CD3ε monoclonal antibody, was able to delay the onset of diabetes by 32.5 months in an autoantibody-positive, high-risk population (2;3). In a longitudinal follow-up analysis of this study (3), teplizumab treatment improved the mean C-peptide area under the curve (AUC) over a 6-month period after a decline in C-peptide responses before study entry. Treatment also reversed the decline in insulin secretion observed before enrollment.

[0134] These findings suggested that metabolic endpoints may be valuable to obtain more accurate information about the effects of teplizumab. Thus, the utility of metabolic endpoints to study teplizumab effects could potentially be generalized to evaluate preventive treatments in other clinical trials. C-peptide responses from oral glucose tolerance tests or mixed meal tolerance tests (OGTT; MMTT) have been primarily used to assess β-cell function both before and after the diagnosis of diabetes (4). However, today, several studies have shown that a combination of stimulated glucose / C-peptide markers improves the prediction of type 1 diabetes, the identification of heterogeneity within the autoantibody-positive population, and the detection of subtle changes in β-cell function (5-11).

[0135] Therefore, we reasoned that the combination of these measures would be used to address two important questions: (1) whether substantial teplizumab effects on β-cell function are seen within 3 months after a 14-day treatment course among individuals at high risk for type 1 diabetes, and if so, whether this effect persists for at least 6 months; and (2) whether rapid β-cell attenuation is possible within 3 months among high-risk individuals if teplizumab is not administered. We addressed these questions using two composite glycemic / C-peptide markers, Index60 (8, 9) and C-peptide AUC / glycemic AUC ratio. In addition, we used a glycemic / C-peptide response curve (GCRC) derived from an OGTT on a two-dimensional grid (2dgrid). This recently introduced method expands the concept of combining glycemic and C-peptide measures by utilizing the fusion of qualitative and quantitative methods. This method has already facilitated studies of the metabolic natural history of type 1 diabetes (12), the metabolic heterogeneity of the disorder at the time of diagnosis (13), and the metabolic effects of potential preventive interventions (14). In another study, GCRC (by MMTT) was the basis for studying the association of metabolic changes with microRNAs following the diagnosis of type 1 diabetes (15).

[0136] The findings would indicate that teplizumab effectively preserves and improves beta-cell function immediately after treatment in individuals at high risk for type 1 diabetes, and that this effect is sustained. The findings also show that none of the cases in the placebo group were diagnosed within 3 months after randomization, although significant metabolic deterioration was already observed during this period. Furthermore, the findings support that the tandem use of a combined glycemic / C-peptide endpoint with GCRC provides qualitative and quantitative insights into the timing and magnitude of preventive treatment effects that are missed by the use of diagnostic endpoints alone in type 1 diabetes prevention trials.

[0137] Research design and methods Study procedure and design The design of the phase 2, randomized, placebo-controlled, double-blind TrialNet TN10 anti-CD3 prevention study (NCT01030861) has been reported in detail previously (2). Institutional review board approval was obtained at each participating institution with written informed consent and assent prior to study entry. Inclusion criteria were age ≥8 years at randomization, history of relatives with type 1 diabetes, stage 2 diabetes [positive titers for ≥2 islet autoantibodies (anti-glutamic acid decarboxylase 65, microinsulin, anti-islet antigen 2, anti-zinc transporter 8, and / or islet cytoplasmic antibodies), and dysglycemia]. HbA1c levels were within the normal range [median (interquartile range) for teplizumab: 5.2% (4.9%-5.4%); median (interquartile range) for placebo: 5.3% (5.1%-5.4%)]. Participants were randomly assigned to receive teplizumab or saline, administered as an IV infusion, over a 14-day outpatient course. OGTT C-peptide / glucose levels were determined by Northwest Lipids Research Laboratories using the TOSOH C-peptide and Roche glucose assay. OGTT glucose levels within the diabetic range were excluded from this analysis.

[0138] AUC values ​​for C-peptide and blood glucose were calculated using the trapezoidal rule (16). C-peptide AUC / blood glucose AUC ratio values ​​were obtained by calculating the ratio × 100. Index60 was calculated as 0.3695 × (log fasting C-peptide [ng / mL]) + 0.0165 × blood glucose at 60 min (mg / dL) + 0.3644 × C-peptide at 60 min (ng / mL) (17). Glucose and C-peptide response curves (GCRCs) were generated by plotting the mean blood glucose (y-axis) and mean C-peptide (x-axis) values ​​from the OGTT (at 30, 60, 90, 120 min, and 4 h) on a two-dimensional grid.

[0139] Analysis component Figures 3A-3C include six key components used in the analysis of metabolic changes: a two-dimensional grid with blood glucose on the y-axis and C-peptide on the x-axis, GCRCs, centroids (centers of GCRCs), vectors, direction quadrants for the vectors, and angles. Figure 3A shows two hypothetical GCRCs from the same individual plotted on a two-dimensional grid from mean blood glucose and mean C-peptide values ​​from an OGTT at 30, 60, 90, and 120 minutes. One of the GCRCs is typical 6 months before diagnosis, while the other is typical at the time of diagnosis. The centroids for each GCRC were calculated (see formula). A significant change in the location of the GCRC from 6 months before diagnosis to the time of diagnosis is evident, pointing to a metabolic decline. The arrow is a vector for the change in location from the GCRC centroid 6 months before diagnosis to the GCRC centroid at the time of diagnosis. Note that the direction and magnitude of the vectors are a function of the decrease in C-peptide and increase in blood glucose from baseline to 6 months later.

[0140] In Figure 3B, a right triangle has been superimposed on Figure 3A. The right triangle is formed from a vector (the hypotenuse) and the changes in blood glucose (the vertical side) and C-peptide (the horizontal side). The formation of the right triangle provides a means for calculating the vector angle. As shown in the figure, the calculated angle for this analysis is defined as the angle between the vector (the hypotenuse) and the horizontal side of the right triangle.

[0141] Figure 3C shows hypothetical examples of vectors for each of the four orientation quadrants: right lower quadrant; right upper quadrant; left upper quadrant; left lower quadrant. All of these are taken from the center of gravity at baseline when the changes in blood glucose and C-peptide are fixed at zero. Thus, the orientation quadrant for the vector depends on whether the changes in blood glucose and C-peptide are positive or negative. The calculated angle between the horizontal line and the vector is also shown.

[0142] To provide a quantitative comparison to complement the visual comparison of GCRC, we developed two new endpoints based on vectors and angles that indicate the change in GCRC movement over 6 months: WQE (Within Quadrant Endpoint) and ODE (Ordinal Directional Endpoint). Both endpoints utilize Cox regression modeling based on the movement of GCRC into four potential quadrants that reflect the changes in blood glucose and C-peptide. For information on the development of these two new endpoints, please refer to Figure 4.

[0143] Formula for calculating center of gravity CPEP center of gravity=(1 / 3)×(((CPEP30+CPEP60)×((CPEP30×GLUC60)-(CPEP60×GLUC30)))+((CPEP60+CPEP90) GLUC90)-(CPEP90×GLUC60)))+((CPEP90+CPEP120)×((CPEP90×GLUC120)-(CPEP120×GLUC90)))+((CPEP120+CP EP30)×((CPEP120×GLUC30)-(CPEP30×GLUC120)))) / (((CPEP30×GLUC60)-(CPEP60×GLUC30))+((CPEP60×GLUC 90)-(CPEP90×GLUC60))+((CPEP90×GLUC120)-(CPEP120×GLUC90))+((CPEP120×GLUC30)-(CPEP30×GLUC120))) GLUC center of gravity = (1 / 3)×((GLUC30+GLUC60)×((CPEP30×GLUC60)-(CPEP60×GLUC30)))+((GLUC60+GLUC90)×((CPEP60× GLUC90)-(CPEP90×GLUC60)))+((GLUC90+GLUC120)×((CPEP90×GLUC120)-(CPEP120×GLUC90)))+((GLUC120+GL UC30)×((CPEP120×GLUC30)-(CPEP30×GLUC120)))) / (((CPEP30×GLUC60)-(CPEP60×GLUC30))+((CPEP60×GLUC 90)-(CPEP90×GLUC60))+((CPEP90×GLUC120)-(CPEP120×GLUC90))+((CPEP120×GLUC30)-(CPEP30×GLUC120)))

[0144] Development of 6-month WQE (Within Quadrant Endpoint) and 6-month ODE (Ordinal Directional Endpoint) The following sections describe the development of two new endpoints that will be used together in the analysis and their formulation.

[0145] Basis for selecting endpoints for analysis Potential endpoints were first examined for their prediction of type 1 diabetes. Potential endpoints predicting type 1 diabetes were then evaluated for their performance in detecting oral insulin treatment effects in the combined DPT-1 / Trial Net oral insulin study cohort (n=208; no study-by-treatment interaction was found). Among the endpoints studied, WQE (Within Quadrant Endpoint) and ODE (Ordinal Directional Endpoint) predicted type 1 diabetes in 281 DPT-1 participants in the oral insulin group or parenteral insulin control group (p<0.001 for uncorrected WQE, p=0.001 for uncorrected ODE; p<0.001 for both WQE and ODE after correction for blood glucose AUC, C-peptide AUC, age, and BMI). Although other endpoints also predicted type 1 diabetes, WQE and ODE were superior in detecting oral insulin effects. Table 4 shows the comparison of WQE (p<0.001) and ODE (p=0.005) between the placebo group and the oral insulin group after adjustment for baseline blood glucose AUC, C-peptide AUC, age, and BMI. Based on these findings, we used WQE and ODE to statistically evaluate the effect of early teplizumab.

[0146] WQE (Within Quadrant Endpoint) The full 360° continuum had poor predictive ability for type 1 diabetes. Therefore, we explored the possibility that risk prediction might be enhanced by dividing the 360° continuum into its four directional quadrants, ranging from 0° to 90°. Each directional quadrant would be considered to represent its own characteristic risk, which, when incorporated together in the model, predicts the overall risk. The directional quadrants are: Upper Right Quadrant (RUQ) Upper Left Quadrant (LUQ) Lower Right Quadrant (RLQ) Lower left quadrant (LLQ) is specified as

[0147] As shown in FIG. 4, angles were calculated from the right triangle formed according to the directional quadrants of each change vector. For LUQ and RLQ, the calculated angles are negative, so they were converted to positive. The percent change in blood glucose centroid from baseline to 6 months on the y-axis and the percent change in C-peptide centroid from baseline to 6 months on the x-axis were used to calculate the angles. The hypotenuse of the triangle represents the distance from the GCRC centroid at baseline to the GCRC centroid at 6 months (i.e., the magnitude of the vector for change). The formulas for the calculated angles and hypotenuse are shown below: radian = arctangent (% change in blood glucose / % change in C-peptide) Degrees = Radians x 57.296 Hypotenuse = Square root of ((% change in blood glucose × % change in blood glucose) + (% change in C-peptide × % change in C-peptide)) (The formula uses percent changes in blood glucose and C-peptide instead of actual measurements to normalize the units of the sides of the triangle).

[0148] Using data from the control group of the DPT-1 / TrialNet parenteral insulin / oral insulin trial (n=281), we developed a Cox regression model that incorporates the calculated angle of change over 6 months in each quadrant as an independent variable for predicting type 1 diabetes. Because each change vector falls in only one of the quadrants, the values ​​in the other quadrants were assigned as 0. Based on this paradigm, we found that the model significantly predicted type 1 diabetes. However, we also found that if the calculated angle for a particular quadrant was subtracted from 90°, the other models were also predictive.

[0149] FIG. 4 shows how the vectors, quadrants, and angles were defined. FIG. 4 also hypothetically shows that the angles utilized for the final model incorporated the calculated angles of percent change in LUQ and RLQ, and the calculated angles of percent change in LLQ and RLQ subtracted from 90°. In addition, we observed that the model better predicted type 1 diabetes by correcting the model coefficients for baseline risk with the DPT-1 Risk Score (10) (DPTRS). Thus, the final model coefficients are based on the correction for DPTRS. The following formula shows the coefficients of the directional quadrant angle (qangle) used for the model to detect the maximum difference between the oral insulin group and the placebo group (p<0.001). WQE=0.02455×qangle1+0.01464×qangle2+0.00831×qangle3-0.00465×qangle4 [Let qangle1=RUQ, qangle2=LUQ, qangle3=LLQ, and qangle4=RLQ] (for an individual, three of the four orientation quadrants will always be negative, so we used an indicator variable coded as "0").

[0150] The following outline shows the steps required to calculate WQE: Calculation of blood glucose / C-peptide coordinates for the GCRC centroid at baseline and 6 months. Conversion of change in blood glucose / C-peptide centroid coordinates to percent change. Identify the directional quadrant for the vector between the baseline coordinate and the 6-month coordinate. · Calculate the angle between a horizontal line and a vector in a quadrant using the standard formula based on a right triangle. · Convert negative angles in direction quadrants 2 and 4 (qangle2 and qangle4) to positive angles. For qangle1 and qangle2, use the calculated angle. In the model, use (90° - calculated angle) for qangle3 and (90 - qangle4).

[0151] The procedure for converting angles from negative to positive, and subtracting angles from 90°, is given below: If the vector for the change in center of gravity is within RUQ, then qangle1 = the calculated angle. If the vector for the change in center of gravity is in LUQ, then qangle2 = calculated angle x (-1). If the vector for the change in center of gravity is within the LLQ, then qangle3 = 90 - the calculated angle. If the vector for the change in center of gravity is within the LLQ, then qangle4 = 90 - calculated angle x (-1).

[0152] Example for WQE: An individual's orientation from the GCRC centroid at baseline to the GCRC centroid at 6 months is within the LLQ with qangle of 32°. WQE=0.00831×(32)=0.266 (0.00831 is the regression coefficient for the LLQ orientation quadrant).

[0153] Ordinal Directional Endpoint (ODE) at 6 months Using a 360° scale, we assigned values ​​to four quadrants according to previous evidence about the temporal directionality of progression to type 1 diabetes over time, as indicated below (15). Lower Right Quadrant (RLQ): 0° Lower left quadrant (LLQ): 90° Upper Right Quadrant (RUQ): 180° Upper Left Quadrant (LUQ): 270°

[0154] The value was added to the value of qangle obtained from the WQE model. The sum was then divided by 360 to create a scale with a maximum of 1.00.

[0155] The outline of the steps required to compute an ODE is the same as that required to compute a WQE, except that instead of inserting the qangle value into the model, qangle is added to the specified value indicated above for the direction quadrant.

[0156] Example for ODE: The direction of an individual's vector from the GCRC centroid at baseline to the GCRC centroid at 6 months is within a LUQ with qangle of 49°. The 6 month ODE for this individual is: 270°+49°=319° / 360°=0.87 units [where 270° represents the quadrant value specified for the LUQ and 49° represents the angle value within the LUQ] It is.

[0157] Potential endpoints were first examined for their prediction of type 1 diabetes. Potential endpoints predicting type 1 diabetes were then evaluated for their performance in detecting oral insulin treatment effects in the combined DPT-1 / Trial Net oral insulin study cohort (n=208; no study-by-treatment interaction was found). Among the endpoints studied, WQE (Within Quadrant Endpoint) and ODE (Ordinal Directional Endpoint) predicted type 1 diabetes in 281 DPT-1 participants in the oral insulin group or parenteral insulin control group (p<0.001 for uncorrected WQE, p=0.001 for uncorrected ODE; p<0.001 for both WQE and ODE after correction for blood glucose AUC, C-peptide AUC, age, and BMI). Although other endpoints also predicted type 1 diabetes, WQE and ODE were superior in detecting oral insulin effects. Table 4 shows the comparison of WQE (p<0.001) and ODE (p=0.005) between the placebo group and the oral insulin group after adjustment for baseline blood glucose AUC, C-peptide AUC, age, and BMI. Based on these findings, we used WQE and ODE to statistically evaluate the effect of early teplizumab.

[0158] [Table 1]

[0159] statistical analysis Groups were compared using t-tests and chi-square tests. Linear regression was used to adjust for variance, while proportional hazards regression was used to develop models for the endpoints. Gender was not included as a covariate in the analysis. All analyses were performed using the statistical program SAS (version 9.4). A two-sided p-value of <0.05 was considered statistically significant.

[0160] result The baseline characteristics of the participants are shown in Table 5. No significant differences were found between the placebo and teplizumab groups for any demographic measures or baseline OGTT blood glucose or C-peptide levels. Of the 76 participants, 29 placebo-treated and 41 teplizumab-treated individuals had sufficient OGTT data for analysis at 29 months after randomization, and 24 placebo-treated and 44 teplizumab-treated individuals at 24 months after randomization. Five individuals from the placebo group were excluded from the analysis of OGTT at 6 months due to a diagnosis of diabetes (3 individuals) or an OGTT blood glucose value in the diabetic range but not meeting the diagnostic criteria for OGTT of being in the diabetic range on two consecutive occasions (2 individuals).

[0161] [Table 2]

[0162] Assessment of metabolic response by GCRC at 3 and 6 months after treatment To determine whether there is early evidence of the effect of teplizumab on beta cell function after treatment, we compared the change in GCRC at 3 months after randomization between the placebo and teplizumab groups. In Figures 1A and 1B, vectors for the change in centroid at the 3-month visit after randomization were plotted for each individual in the placebo and teplizumab groups. In these vector plots, the vectors of 11 of 29 individuals (37.9%) in the placebo group versus 6 of 41 individuals (14.6%) in the teplizumab group were directed toward the upper left quadrant (decreased C-peptide and increased blood glucose), suggesting worsening metabolic function. This was in contrast to 11 of 41 (26.8%) individuals in the teplizumab group versus 2 of 29 (6.9%) in the placebo group whose vectors were directed to the right lower quadrant (increased C-peptide and decreased blood glucose), suggesting improved metabolic function. Within all four quadrants, the frequencies of placebo- versus teplizumab-treated participants were significantly different (overall p = 0.045) (Table 1).

[0163] [Table 3]

[0164] 1C-1D depict the GCRC constructed according to the mean values ​​of blood glucose and C-peptide for each OGTT time point, as well as vectors pointing to the change in GCRC centroid at 3 months after randomization. In the placebo group, by 3 months, the vector for the change in GCRC centroid over this period was directed toward the upper left quadrant, revealing progressive metabolic dysfunction (decreased C-peptide and increased blood glucose). In contrast, the vector for the change in GCRC centroid in the teplizumab group showed a nearly opposite direction toward the lower right quadrant (increased C-peptide and decreased blood glucose). The magnitude of the effect of teplizumab was evident in the directional difference of 153° (out of a maximum of 180°) between the placebo and teplizumab vectors.

[0165] The changes in AUC Ratio and Index60 from baseline to 3 months were consistent with large differences in the direction of the vectors. Both changes were significantly different between placebo and teplizumab (p<0.01 after adjustment for baseline parameters, age, and BMI; Table 2). Furthermore, there was evidence of improvement in the teplizumab group: AUC Ratio increased (p<0.01) and Index60 decreased (p<0.05) (paired analyses could not be adjusted for multicollinearity).

[0166] [Table 4]

[0167] Figures 1C-1D also note the striking structural change in GCRC in the placebo group at 3 months after randomization, with an increasing upward slope between 30 and 60 minutes, typical of the ongoing transformation to type 1 diabetes (12), whereas the slope in the teplizumab group was nearly the same.

[0168] The patterns of the individual vectors at 6 months were similar to those at 3 months. As shown in Figures 1E-1F, the direction of the individual vectors was leftward and upward in the placebo group, suggesting metabolic deterioration, whereas the rightward and downward movement in the teplizumab group suggests metabolic improvement. Thus, a high percentage of the placebo group directed vectors to the upper left quadrant (45.8% of placebo vs. 11.4% of teplizumab), whereas a high percentage of the teplizumab group directed vectors to the lower right quadrant (8.3% of placebo vs. 34.1% of teplizumab). Differences were also evident in the vectors of GCRC centroid movement by OGTT mean (Figures 1G-1H). At 6 months after randomization, the difference in direction between placebo and teplizumab vectors was 138°. The differences in vector frequency between groups were significant among all four quadrants (overall p=0.004) (Table 1).

[0169] Between-group differences in changes in AUC Ratio and Index 60 were also significant but not large (p = 0.005 and p = 0.021, respectively, after adjustment; Table 2). Within the teplizumab group, an increase in AUC Ratio from baseline to 6 months was also evident (p < 0.01), but Index 60 did not decrease significantly.

[0170] In Figures 1G-1H, it is clear that by 6 months after randomization, the GCRC shapes became substantially more pathological, taking on a shape that closely resembled the diagnostically characteristic GCRC shape (12). Specifically, the placebo GCRCs at 30-90 minutes were nearly linear, with a less downward slope at 60-90 minutes. The magnitude of change in GCRC shape for teplizumab was much smaller.

[0171] Quantitative assessment of treatment effects using vector angles within orientation quadrants The above analysis showed clear differences in GCRC vectors between placebo and teplizumab groups in the teplizumab study within 3 months after 14 days of treatment and at least until 6 months later. These differences were confirmed by the difference in Index60 and AUC Ratio between groups. However, these composite blood glucose / C-peptide scales were not based on the directionality of vectors, which indicates the change in GCRC. Therefore, the inventors sought to develop quantitative endpoints that more directly indicate the difference in vectors between placebo and treatment groups. Two such endpoints were developed: WQE (Within Quadrant Endpoint) and ODE (Ordinal Directional Endpoint) (see research design and methods). Both endpoints were derived from the change in GCRC centroid position at 6-month intervals, which is the shortest interval between OGTTs available for analysis in Diabetes Prevention Trial-Type 1.

[0172] The visual difference in GCRC movement between the placebo and treatment groups from baseline to 3 months was statistically confirmed by ODE and WQE (Figures 2A and 2B). ODE values ​​were significantly lower for the teplizumab group (p<0.05 after adjustment). WQE values ​​were also significantly lower in the teplizumab group before adjustment (p<0.05), but showed only a trend toward a difference after adjustment (p=0.072).

[0173] The differences in WQE and ODE between the placebo and teplizumab groups at 6 months were significantly greater than at 3 months: WQE was significantly lower for the teplizumab group (p<0.01), as was ODE (p<0.01). Table 2, which summarizes the differences between the placebo and teplizumab groups according to the endpoints, shows that the Index60 and AUC Ratio differed more between the groups at 3 months, whereas WQE and ODE differed more at 6 months.

[0174] conclusion The teplizumab trial showed that a single-agent treatment course could delay the onset of type 1 diabetes (2). However, this trial and other prevention trials that utilized standard time-to-diagnosis endpoints were long-term. Teplizumab was also highly effective in delaying type 1 diabetes, but lacked information about the timing of its effect and its impact on metabolic status. Thus, we used existing and new metabolic markers as endpoints to obtain this information. Such an early readout would not only help understand the effect of the prevention treatment on beta cell function, but could also possibly result in a shorter prevention trial.

[0175] Measurement of C-peptide AUC in response to oral glucose prediagnosis or to a mixed meal postdiagnosis is often used to assess insulin responsiveness; however, C-peptide AUC is not necessarily the most sensitive measure to identify changes in β-cell function. Studies suggest that the loss of C-peptide in type 1 diabetes is best presented and understood in the context of glycemic changes (5-11). In this study, we used a novel approach that merged qualitative and quantitative information to better understand insulin secretion dynamics in response to glycemia. Using this approach, findings provided strong evidence that teplizumab abrogates severe β-cell killing in a high-risk population and likely improves function by 3 months after treatment. Moreover, the effect persists for at least 6 months after treatment. These findings have important implications, as they indicate that the effect of teplizumab is rapid enough to have a high impact even in the advanced stages of metabolic deterioration prediagnosis.

[0176] GCRCs and their centroids, along with vectors and their angles, played a major role in the analysis. The use of these elements resulted in a visual contrast between the declining metabolic state of the placebo group and the clear improvement of the teplizumab group, as evident from the GCRC changes on the two-dimensional grid. These elements were also used as the basis for developing new endpoints, WQE and ODE, which were used in the quantitative comparison of changes between the placebo and teplizumab groups. Together with the AUC Ratio and Index60, these endpoints confirmed the visual impression that teplizumab prevented the rapid metabolic decline in high-risk individuals immediately after 14 days of treatment at baseline. Table 3 summarizes how methods based on GCRC movement and shape enhanced our understanding of the timing, magnitude, and potential clinical importance of the teplizumab effect.

[0177] [Table 5]

[0178] Findings from these analyses highlight the advantage of using vectors, in addition to scalars, as metabolic endpoints for the analysis of treatment effects. Whereas previous analyses of preventive measures have relied on scalars that only provide information about magnitude, vectors provide information about direction in addition to magnitude. Vectors of GCRC movement on a two-dimensional grid clearly added information that was not identified from scalar endpoints alone.

[0179] We have already used vectors of GCRC changes as evidence of oral insulin's effect to preserve β-cell function in a post-hoc analysis of DPT-1 and TrialNet oral insulin trials among individuals at high risk for type 1 diabetes (14). Interestingly, the vectors in the present teplizumab analysis were much more separated between the placebo and treatment groups than in the oral insulin analysis. The difference in vector direction between the placebo and teplizumab groups in the teplizumab study ranged from the upper left quadrant (placebo) to the lower right quadrant (teplizumab), whereas the difference between the placebo and oral insulin vectors was mostly restricted to the upper right quadrant. The increased separation of vectors in the teplizumab study could be based on differences in therapeutic mechanisms and / or differences in the magnitude of effect between teplizumab and oral insulin. If vectors are overlooked and one relies only on scalars, the analysis of the effectiveness of preventive treatments would be incomplete.

[0180] Because the endpoints in the teplizumab trial were chosen for high risk, detection of treatment effects by the endpoints WQE and ODE may not generalize to trials in other stages of disease. It is also entirely possible that other endpoints of GCRC centroids of change and their vectors may prove to be better endpoints than WQE and ODE. However, the performance of these endpoints in analyses validating the visual impression derived from GCRC suggests that the combined qualitative and quantitative use of vectors to examine metabolic changes may be a valuable approach to assess the effects of preventive treatments.

[0181] It is noteworthy that this study is also the first to report the use of change in Index60 as an endpoint to support metabolic effects in the analysis of a T1D prevention study. Overall, these results and previous results (14) suggest that multiple metabolic endpoints, including Index60, AUC ratio, and WQE and ODE, which combine changes in glycemia and C-peptide, may provide a readout for treatment effects in type 1 diabetes prevention studies. The subtle variability between treatment groups detected between the oral insulin and teplizumab studies may reflect differences in study populations or therapeutic interventions. Changes in Index60 and AUC ratio were more different between placebo and teplizumab groups from baseline to 3 months than WQE and ODE, whereas the opposite was evident from baseline to 6 months. Since the development of both WQE and ODE was based on 6-month data, it is not surprising that they performed better from baseline to 6 months. Analysis of the teplizumab study suggested that Index60 and AUC ratio may possibly be more sensitive for detecting early effects, but this may not be generalizable to other trials. The selection of metabolic endpoints for prevention trials will depend on factors that may affect their relevance and performance, such as the target population, objectives, intervention, and study design. The advantage of the WQE and ODE over other measures is that they complement the precise visual impression derived from the GCRC (summarized in Table 3).

[0182] The magnitude of change in metabolic measures at 0-30 min is much larger than that at each of the other time intervals, so we do not incorporate it into the GCRC. Its incorporation would therefore minimize the visualization at 30-120 min. Similarly, from a quantitative perspective, the 0-30 min interval would overweight the calculation of centroids and vectors, which would further complicate the analysis. Although we do not incorporate C-peptide / blood glucose measures at 0-30 min into the GCRC, we did correct for baseline C-peptide AUC and blood glucose AUC values ​​in the analysis. Now that we have developed quantitative measures to complement the visualization of the GCRC with their centroids and vectors, an important future direction will be to study the impact of changes at 0-30 min on changes in GCRC morphology and location.

[0183] The applicability of short-term interim metabolic endpoints to prevention trials will require further study. Primary metabolic endpoints have been used successfully in inception type 1 diabetes trials, where follow-up over a 1-year period is usually specified to evaluate treatment efficacy for delaying further loss of insulin secretion. Positive findings on metabolic outcomes in these inception trials have been used to justify treatment in prediagnostic prevention trials (18-21). Our findings suggest that information from prediagnostic short-term prevention trials may also be used to determine whether larger prediagnostic prevention trials are warranted for a particular treatment.

[0184] Short-term metabolic endpoints are likely to have several other uses for assessing prediagnostic prevention treatments. Short-term metabolic endpoints will also be used for stopping rules in trials if a prespecified effect is not reached. One novel approach to using metabolic endpoints would be to use them in combination with diagnostic endpoints. It is even envisioned that metabolic endpoints will be used as primary endpoints for certain trials. As revealed in this study, these endpoints may also provide important pharmacological information derived from the trial, such as the timing of treatment effects.

[0185] A previous longitudinal study of teplizumab (3) examined the mean treatment effect of teplizumab on C-peptide AUC over a 6-month period. This study did not use GCRC methods or a combined glycemic / C-peptide endpoint to assess the specific timing of teplizumab effects, nor did it demonstrate the importance of going beyond the prevention of severe loss of β-cell functionality with teplizumab use in high-risk individuals. As already mentioned, an analysis of an oral insulin trial (14) utilized GCRC vectors, but to a much lesser extent.

[0186] This study had some limitations. Three individuals in the placebo group were excluded from the 6-month analysis because they had already developed diabetes at the 6-month time point. This not only reduced the sample size, but also likely led to the appearance of less severe metabolic decline in the placebo group. Such bias would weaken, rather than enhance, the effect of teplizumab at 6 months. Because all teplizumab trial participants were required to be positive for multiple islet autoantibodies along with metabolic abnormalities, future analysis will be required to determine whether our findings are applicable to risk populations with less severe baseline disease, such as individuals testing positive for a single islet autoantibody.

[0187] GCRC vectors in the lower right / upper left quadrants are likely to reflect improved or worsening metabolic status, whereas vectors in the upper right / lower left quadrants may reflect more moderate changes consistent with alterations in insulin secretion kinetics or insulin sensitivity. However, to truly define these changes, a gold standard measure of beta cell function, such as a glucose-enhanced arginine clamp, would be required. Quantitative treatment group comparisons (Table 2) were adjusted for BMI and age, but because of beta cell dysfunction in this population, we chose not to adjust for OGTT-based modeling measures of insulin resistance (22).

[0188] In DPT-1, both WQE and ODE were significantly associated with the progression of diabetes; however, detection of treatment effects by metabolic endpoints is not purely a function of the ability of the metabolic endpoint to predict type 1 diabetes. For example, an individual may improve C-peptide response to treatment and still proceed to develop diabetes, whereas conversely, another individual may not show improvement in C-peptide secretion to treatment but will not develop type 1 diabetes at follow-up. Thus, a crucial future direction is the analysis of the relationship between the ability of an endpoint to detect treatment effects versus its ability to predict diabetes.

[0189] Although the development of the WQE / ODE endpoints involved some complexity, their application in research will be primarily based on standard formulas for the calculation of angles. Thus, although we have incorporated explanations in this paper to describe the development of this novel method, in practice, the implementation of these measurements will only involve the use of formulas, as with other accepted indices, such as the Index60 (17).

[0190] In conclusion, the analysis of glycemic / C-peptide changes based on changes in GCRCs and their centroids on a two-dimensional grid provided visual evidence of the effect of teplizumab treatment early enough to prevent the rapid decline of β-cell function and possibly even improve function in a population at high risk for type 1 diabetes. This was statistically confirmed by a combined glycemic / C-peptide endpoint and a new endpoint derived from a vector of GCRC changes. These findings suggest that changes in GCRC grid location and shape, along with corresponding quantitative measures of directionality, should be incorporated into the analysis of type 1 diabetes prevention trials. Furthermore, these findings add to the growing body of evidence that endpoints combining both glycemic and C-peptide are fundamental to our understanding of treatment effects in prevention trials. Future directions will involve the refinement of the application of these endpoints to facilitate the evaluation of prevention treatments in both small and large studies.

[0191] Modifications and variations of the disclosed methods and compositions described will be apparent to those skilled in the art without departing from the scope and spirit of the disclosure. Although the disclosure has been described in connection with specific embodiments, it should be understood that the claimed disclosure should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes of carrying out the disclosure are contemplated and understood by those skilled in the art within the scope of the disclosure, as expressed by the following claims.

[0192] Incorporation by Reference All patents and publications mentioned in this specification are herein incorporated by reference to the same extent as if each individual patent and publication was specifically and individually indicated to be incorporated by reference.

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Claims

[Claim 1] 1. A method for prognosticating responsiveness to a therapeutic or prophylactic agent for treating or preventing type 1 diabetes (T1D), comprising: administering a therapeutic or prophylactic agent to a subject in need thereof; and determining a change vector in the glucose and C-peptide response curve (GCRC) by plotting the change over time in the mean blood glucose and mean C-peptide levels from an oral glucose tolerance test on a two-dimensional grid, wherein the direction of the change vector toward an increase in C-peptide and a decrease in blood glucose indicates metabolic improvement; A method comprising:

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