# Interdisciplinary Systems-based Training for Precision Nutrition

> **NIH NIH T32** · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · 2024 · $315,081

## Abstract

Project Summary/Abstract
Interdisciplinary Systems-based Training for Precision Nutrition
The future workforce and current thought leaders in precision nutrition need in-depth knowledge of artificial
intelligence (AI) to harness the power of modern technologies such as multi-omics and wearables to combat
diet-related chronic diseases related to the mission of the National Institute of Diabetes and Digestive and Kidney
Diseases (NIDDK). Arizona State University (ASU), through the College of Health Solutions (CHS), is poised to
meet this need through its multidisciplinary, transformative new structure. CHS has organized its research
enterprise and academic programs into “Translational Teams,” wherein faculty, trainees, and community
stakeholders work together to more rapidly translate basic discovery into practice. We propose a predoctoral
and postdoctoral training program - rooted in foundational disciplines of nutrition and big data analytics - that will
focus on courses and practical experiences related to precision nutrition. Students will be drawn from long-
standing and successful PhD programs in Exercise & Nutritional Sciences and Biomedical Informatics, both of
which are already housed within CHS and have strong collaborative ties among faculty and programmatic
requirements. Our training program will provide an interdisciplinary, comprehensive training in precision nutrition
topics, reflecting the expertise of our mentor team in nutrition and metabolism (obesity and diabetes; microbiome
and functional foods; energy balance; wearable technologies; and digital health interventions) and artificial
intelligence and systems modeling (multimodal and multiscale data integration; systems biology; actionable and
interpretable AI; AI-based personalization ; time-series and mobile device analytics; and geographic information
systems). The training program will support nine new predoctoral students and two postdoctoral students, each
of whom will be mentored by a multidisciplinary pair of accomplished nutrition and big data analytics scientists.
All trainees will be provided a hybrid-delivered “bootcamp” experience in nutrition and data science upon entry
into the program to build a strong foundation for interdisciplinary training. Trainees will then sample from relevant
courses in statistical and machine learning, energetics, nutrigenomics, clinical applications, adaptive trial design,
etc... The training will be further supported by regular seminar series and journal clubs; experiential rotations;
annual symposia; and community, industry, and healthcare-based internships. As an institution that serves >25%
Hispanic population, our training program will emphasize recruitment of this and other underrepresented student
populations and engage with disadvantaged communities. We will leverage our rich training environment of
ongoing federally-funded projects, along with our collaborative partners at the Phoenix VA Healthcare System,
and the NIDDK Phoenix E...

## Key facts

- **NIH application ID:** 10917234
- **Project number:** 5T32DK137525-02
- **Recipient organization:** ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- **Principal Investigator:** Li Liu
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $315,081
- **Award type:** 5
- **Project period:** 2023-09-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10917234

## Citation

> US National Institutes of Health, RePORTER application 10917234, Interdisciplinary Systems-based Training for Precision Nutrition (5T32DK137525-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10917234. Licensed CC0.

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