# Development of An Automated High-Throughput Dried Blood Spot Assay to Facilitate Large Scale Screening for Type 1 Diabetes Risk

> **NIH NIH R44** · ENABLE BIOSCIENCES, INC. · 2020 · $741,180

## Abstract

Type 1 diabetes (T1D) is a chronic autoimmune disease that affects millions of children and adults in the
US. Up to 40% of T1D patients are diagnosed in the emergency room with life-threatening diabetic
ketoacidosis (DKA), resulting in severe clinical complications and a substantial economic burden.
Programs that screen for blood-borne markers of early-stage T1D (anti-islet cell autoantibodies) can
significantly diminish the incidence of DKA and improve patient quality of life. However, large-scale
implementation of such screening campaigns is hindered by the high cost and low throughput of
radioimmunoassay (RIA), the gold-standard method for measuring anti-islet autoantibodies. Moreover, a
significant portion of screening program costs are associated with phlebotomy, cold-chain storage and
shipping. To address this, Enable Biosciences aims to develop a cost-effective, multiplex, high-
throughput and non-radioactive immunoassay to diagnose T1D and screen for individuals at risk for T1D
using low-cost easy-to-collect dried blood spots (DBS). The successful development of this high-
throughput dried blood spot T1D assay can substantially increase the effectiveness of general population-
based T1D screening programs. In a JDRF- and Stanford-supported initiative, we were gratified that a
serum-based Enable assay achieved the highest performance for anti-GAD, anti-IA2 and a close
second-to-highest performance for anti-insulin antibodies in the recent blinded 2018 Islet-cell
Autoantibody Standardization Program (IASP) competition out of 50 participating laboratories.
The IASP data were generated with an automated Enable serum assay using a custom-made Enable
analyzer created in collaboration with Hamilton Robotics. Furthermore, we showed that our manual DBS-
based Enable assay correlated strongly with a serum-based assay (R=0.90-0.96). The concordance as
evaluated by Cohen’s test showed kappa between 0.85-0.89. The positive and negative agreements for
all three aforementioned autoantibodies range from 85%-99%. Notably, we also demonstrated less than
10% degradation of assay signals when DBS cards were stored at 37°C for 4 weeks. Building on these
solid technical achievements, which we consider as our “Phase I-like Results” described in detail in this
proposal, we aim to further automate our DBS assay procedures for high-throughput functionality
including DBS elution and DBS eluent testing using diverse samples, such as those from Stanford
University School of Medicine. We expect to deliver an integrated DBS T1D autoantibody assay
(elution/testing automation device and reagent kits) to serve large screening centers and CLIA-
laboratories. We further plan to obtain CE Mark classification and FDA approval to further decentralize
DBS T1D autoantibody testing to be able to address the important needs of communities, clinicians and
researchers worldwide.

## Key facts

- **NIH application ID:** 10020787
- **Project number:** 5R44DK124009-02
- **Recipient organization:** ENABLE BIOSCIENCES, INC.
- **Principal Investigator:** David Seftel
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $741,180
- **Award type:** 5
- **Project period:** 2019-09-19 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10020787

## Citation

> US National Institutes of Health, RePORTER application 10020787, Development of An Automated High-Throughput Dried Blood Spot Assay to Facilitate Large Scale Screening for Type 1 Diabetes Risk (5R44DK124009-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10020787. Licensed CC0.

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