# Automated Glucose Regulation to improve Diabetes Control and Outcomes for Pregnant Women with Type 1 Diabetes and Fetus

> **NIH NIH R01** · HARVARD UNIVERSITY · 2020 · $751,268

## Abstract

PROJECT ABSTRACT
Pregnancy in patients with type 1 diabetes (T1D) is associated with high maternal and fetal risk. Tight glycemic
control is critical to reduce pregnancy complications. However, achieving the recommended glycemic targets is
very challenging for most pregnant women with T1D. Contemporary closed-loop control or artificial pancreas
(AP) systems can offer optimal solutions to this unmet clinical need. However, diurnal physiological, hormonal
and glucose changes throughout the ~40 week gestation, the changing glycemic risks to fetus and mother and
the stringent regulations about research in this population have limited interventional studies in this cohort to
date. As a result, AP technologies have not been studied in pregnant women with T1D in the US. The consortium
of Harvard/Mayo Clinic/Mt. Sinai and Sansum Diabetes Research Institute aim to develop an AP system that is
customized to the individual needs of pregnant women with T1D and is able to adapt to the physiologic changes
during pregnancy. A series of short-term supervised clinical studies will provide feedback for the system
performance and will indicate required improvements. Through an iterative process, the AP algorithm will be
revised and finalized. The successful completion of the initial studies will lead to a 4-week single arm pregnancy
specific AP study with the option of extension of AP for the duration of the pregnancy. The current studies will
enroll subjects after organogenesis is complete and risk is relatively lower in the 14-28 week pregnancy period.
The overall goal of this project is therefore to create adaptive pregnancy-informed AP technologies, for testing
with subsequent phase 2 and phase 3 randomized clinical trials, in 3 Specific Aims as follows:
 Specific Aim 1: Develop a state of the art automated glucose control system for prolonged use
during all stages of pregnancy in T1D. Leverage clinical information obtained by the analysis of a multicenter
database of glycemic variability, insulin management and outcomes of pregnant women with T1D to design a
cloud based adaptive decision support system (DSS) layer for the AP.
 Specific Aim 2: Evaluate the safety and feasibility of automated glucose control during the second
trimester in a supervised setting for T1D. The control algorithm will be updated to enable real-time glucose
management for pregnant women with time-varying insulin sensitivity profiles. Three clinical studies will be
conducted, two supervised 48 hour and one 1-week home-based study to evaluate the safety and efficiency of
the proposed control strategy and to finalize the algorithm details that will establish a safe AP system tailored for
pregnant women.
 Specific Aim 3: Extended evaluation of automated glucose control during second and third
trimesters of pregnancy in T1D. A prolonged multicenter single arm outpatient AP study (4 weeks and optional
extension phase) will be conducted to evaluate the safety and effectiveness of the developed...

## Key facts

- **NIH application ID:** 9970473
- **Project number:** 5R01DK120358-03
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Eyal Dassau
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $751,268
- **Award type:** 5
- **Project period:** 2018-09-30 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9970473

## Citation

> US National Institutes of Health, RePORTER application 9970473, Automated Glucose Regulation to improve Diabetes Control and Outcomes for Pregnant Women with Type 1 Diabetes and Fetus (5R01DK120358-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9970473. Licensed CC0.

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