# Core B: Data Management and Analysis Core

> **NIH NIH P42** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2022 · $250,929

## Abstract

PROJECT SUMMARY/ABSTRACT – DATA MANAGEMENT AND ANALYSIS CORE
N-Nitrosamines are a family of chemicals that include some of the most potent mutagens known. Many N-
nitrosamines have been shown to be potently carcinogenic in animal models, and some have been deemed
probably human carcinogens. N-Nitrosamines are a major concern for people who live near the Olin Chemical
Superfund Site, because N-nitrosodimethylamine (NDMA) has been found in nearby municipal and private wells.
NDMA is also a concern of the Passamaquoddy Tribe, because the methods used for water treatment are known
to lead to formation of NDMA. The Biomedical Research (BMR) Projects will reveal the health effects of N-
nitrosamines, so as to predict and prevent disease, and the Environmental Science and Engineering (ESE)
Projects will create technology to sense and destroy N-nitrosamines, so as to protect people from these
hazardous chemicals. The mission of the MIT SRP Data Management and Analysis Core (DMAC) is to build and
improve data management, to foster and enable cross-disciplinary collaborations, and to leverage computational
modeling to gain new knowledge. Specific Aim 1 is to continue to improve the MIT-SEEK data management
platform and to create and continuously improve a Comprehensive Data Management Plan. These efforts will
ensure that MIT SRP data are findable, accessible, interoperable, and reusable (FAIR). Specific Aim 2 is to
foster cross-disciplinary collaboration and data integration among Projects and Cores and to share best practices
for a broader impact. Specific Aim 3 is to leverage computational modeling techniques in order to reveal
mechanistic understanding of disease and provide important information about risk. Importantly, the major
goals of the MIT SRP are made possible by a Systems Approach of interactions and interdependencies
among all Projects and Cores. The DMAC is essential to the Systems Approach, because it unifies the team
to focus on data and results from all components, so that effective collaboration is fostered. Constant updating
also provides agility, since researchers can embrace collaborative opportunities as they arise in real time.
Importantly, the DMAC also brings advanced computational modeling techniques so that data streams can be
merged across the program. Integrating knowledge of what, where, and how much N-nitrosamines are in water
with new knowledge of their biological effects will contribute to the understanding of risk and enable prevention
strategies. All research is made possible by Trainees, and their success rests on the Research Translation and
Coordination Core (RETCC). Results from sensors and analytical methods will analyzed by the DMAC, and
these will be made possible by the Community Engagement Core, which will work with community members to
obtain water samples. Finally, through meetings and enrichment activities, the Administrative Core supports the
DMAC both in terms of connectivity within the program, and via int...

## Key facts

- **NIH application ID:** 10351937
- **Project number:** 2P42ES027707-06
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Stuart S Levine
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $250,929
- **Award type:** 2
- **Project period:** 2017-09-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10351937

## Citation

> US National Institutes of Health, RePORTER application 10351937, Core B: Data Management and Analysis Core (2P42ES027707-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10351937. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*