# AlcHepNet DCC UMMS

> **NIH NIH U24** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2022 · $825,889

## Abstract

Abstract
Alcoholic hepatitis (AH) is a leading cause of liver-related morbidity and mortality with a remarkable paucity of
effective therapeutics. NIAAA has sponsored a number of RFAs to form the Alcoholic Hepatitis Network
(AlcHepNet). Collectively, the network will synergize efforts and expertise to better understand AH and develop
novel effective and safe therapies for severe AH. Because of the diversity of studies that will be proposed
under these RFAs, two Data Coordinating Centers will be established to better support these studies efficiently
and effectively to produce high quality reproducible research from each funded study.
This application is for the Data Coordinating Center at the University of Massachusetts Medical School (DCC
UMMS) for AlcHepNet which will provide the statistical and data management leadership to: (1) translational
studies, (2) basic/pre-clinical studies, and (3) pilot clinical trials while using innovations based on previous
experience to facilitate the operations of these studies with shorter timelines and greater quality. The DCC
UMMS Team, housed in the Quantitative Methods Core (QMC) of the Department of Quantitative Health
Sciences, is experienced in both NIH and FDA clinical trials and has implemented a number of proven,
validated approaches in short timeframes and with minimal budgets with increased use of technology and
monitoring tools. The Specific Aims of this proposal are: (1) Efficient and Effective Project Management -
develop a robust infrastructure including communication support and administrative services to facilitate study
objectives; (2) Rigorous Design and Analysis - provide high-level leadership in biostatistics and data
management to the scientific methodology of the DCC UMMS supported studies; and (3) High Quality Study
Implementation - ensure high quality of study results through a rigorous program of quality assurance and
control, study monitoring, and DSMB and regulatory reporting.
Each of these specific aims comprises a set of complex issues that determine efficiency and quality of
implementation. Each will be addressed using multifaceted approaches that can address multiple issues at
once. While there is a need for nimble response to changing needs across studies, there is also need for
measured and documented approaches within the procedural/SOP framework of the DCC UMMS so that each
approach is integrated within the DCC UMMS systems and contributes to higher quality, more reliable data and
reproducible research.

## Key facts

- **NIH application ID:** 10428563
- **Project number:** 5U24AA026968-05
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** Bruce A Barton
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $825,889
- **Award type:** 5
- **Project period:** 2018-08-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428563

## Citation

> US National Institutes of Health, RePORTER application 10428563, AlcHepNet DCC UMMS (5U24AA026968-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10428563. Licensed CC0.

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