Islet Antibody Clinical Trial Enrichment Tool
This quantitative clinical trial enrichment tool helps optimize clinical trial design for therapies to prevent or delay diagnosis of T1D, using islet AAs with other relevant clinical features.
General Information About the Islet Autoantibody Clinical Trial Enrichment Tool
A quantitative clinical trial enrichment tool to help optimize clinical trial design for therapies to prevent or delay diagnosis of T1D, using islet AAs with other relevant clinical features.
Enrichment strategies for clinical trial populations can dramatically increase the power of a trial, relative to similarly designed unenriched trials, potentially facilitating smaller, shorter, and more efficient trials.
In March 2022, the European Medicines Agency adopted a positive Qualification Opinion for the Type 1 Diabetes Consortium’s model-based submission supporting the use of islet autoantibodies (AAs) as enrichment biomarkers for T1D prevention clinical trials. The Qualification Opinions states:
“Positivity to at least 2 of the following islet AAs; insulin/proinsulin autoantibody (IAA), glutamic acid decarboxylase 65 autoantibody (GAD65), insulinoma antigen-2 autoantibody (IA-2), and zinc transporter 8 autoantibody (ZnT8) is qualified for use as enrichment biomarker, in combination with clinical parameters (sex, baseline age, blood glucose measurements from the 120-minute timepoint of an oral glucose tolerance test (OGTT), and hemoglobin A1c levels) in T1D prevention trials targeting individuals at risk of developing T1D.”
To support the implementation of islet AAs, with relevant clinical features, as enrichment biomarkers according to the qualified context-of-use when designing T1D prevention clinical trial, the Type 1 Diabetes Consortium developed a novel tool, the Islet Autoantibody Clinical Trial Enrichment tool.
A cloud-based graphical user interface (GUI) has been developed, which allows a user-friendly experience for scientists and clinicians of all backgrounds to perform simulations based on the model.
An accelerated time failure model which quantifies the time-varying risk of T1D diagnosis in high-risk individuals based on the presence of at least 2 islet AA, sex, baseline age, 120-minute glucose from the oral glucose tolerance test, and baseline HbA1c. A thorough description of the underlying models has been published in Clinical Pharmacology and Therapeutics, and is available here.
- To utilize the islet AAs as enrichment biomarkers for patient selection in clinical trials investigating therapies that are intended to prevent or delay the clinical diagnosis of T1D. These biomarkers, along with additional patient features, such as sex, baseline age, baseline HbA1c levels and the 120-minute time point from an OGTT, can be used as predictors to identify subpopulations at highest risk of a diagnosis of T1D during the course of T1D prevention clinical trials.
- Explore population level trial enrichment approaches using islet autoantibody positivity, along with other relevant patient features for discussion with regulatory authorities
- Determination of potential appropriate trial durations based on pre-specified trial populations
View a recording of the tool’s debut webinar here.
Contact t1dcadmin@c-path.org for more information.
T1DC would like to acknowledge:
This drug development tool runs simulations using a database of synthetic patients generated from aggregated data from the DAISY, TEDDY, and TN01 studies. The TEDDY and TN01 studies were conducted by the TEDDY and TN01 investigators and were supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The data from TEDDY and TN01 used for this tool here were supplied by the NIDDK Central Repositories. This tool was not prepared in collaboration with the investigators of the TEDDY and TN01 studies and does not necessarily reflect the opinions or views of the TEDDY and TN01 studies, the NIDDK Central Repositories, or the NIDDK.
The TEDDY, TN01, DAISY study teams.