Key Dates

Related Announcements

Issued by

Office of Strategic Coordination (Common Fund)

Purpose

Background

Recently, a new NIH precision nutrition research initiative concept called “Nutrition for Precision Health, powered by the All of Us Research Program (NPH)” was presented at NIH Council of Councils. The archived videocast of the Council of Councils meeting is publicly available and can be viewed here (Nutrition for Precision Health discussion begins at 1:54:00). Slides and a brief write-up are also available. This initiative is being refined and developed by NIH for potential implementation in Fiscal Year 2022. The field of precision nutrition, a subset of precision medicine, is to provide more precise and dynamic nutritional recommendations than currently possible through population-wide guidance. To advance this field, research is needed to achieve a deeper understanding of the interplay of human biological systems with the wide variety of factors known to underlie interindividual differences in dietary responses. Individual differences in genetics, epigenetics, microbiome ecologies, biology, nutritional status, behaviors, environments, and socioeconomic influences and disparities may influence these interrelationships; however, their relative importance for driving interindividual variability and predictive values to make precision nutrition recommendations is unclear. NPH posits that insight into these factors can be gained using non-targeted “Omic” approaches (including genomics, epigenomics, proteomics, metabolomics, transcriptomics, metagenomics, etc.) and other targeted inputs (including continuous or discontinuous metabolic, endocrinologic, physiological, cognitive and behavioral measures, surveys, questionnaires, electronic health records, data from social media apps and wearable devices, and community/environmental data, etc.). According to the cleared concept, the data will be broadly accessible in the All of Us Researcher Workbench, which currently supports use of two open-source computer languages, R and Python.

To accomplish the NPH vision, areas of systems science, data science, and computational analytics will be needed. To help identify the gaps and priorities in these areas of systems science and artificial intelligence, the trans-NIH Nutrition for Precision Health Working Group is seeking input from the broad scientific community on the specific needs to help prioritize research activities or community resources that are most likely to propel this field forward for the greater benefit of biomedical research.

Information Requested

This RFI seeks input from individuals and stakeholders throughout the scientific research community and the public regarding any of the following topics:

1. Comments or caveats on disparate data type or format collection (e.g., wearable device data, surveys, electronic health records, -omic and dietary data, diagnostic imaging data) and needs as to how they could be made ‘AI-ready’ (e.g., multifactoriality, well-annotated metadata, sufficient sample size, clear data provenance, etc.) – assuming constant data provenance and quality from data collection and measurement. Comments as to curation needs or requirements for data (e.g., multi-modal and multi-fidelity) collected to make them integrable and ‘AI-ready’ to enable modeling to be actionable. Comments as to important provenance, privacy, and ethical considerations associated with data collected from this program.
2. Consideration of computational and modeling approach challenges, as well as important computational and technical parameters needed to developing algorithms for predicting precision diet recommendations (e.g., when developing algorithms, deciphering scientific discovery, identifying disease-risk biomarkers, or improving accuracy from integrated multi-modal/-parameter data sets). Comments as to collaborative tools for visualization of multiscale (e.g., temporal, biological scale) and multi-modal data as well as other analyses to aid research or implementation of discovery resulting from the initiative.
3. Computational, analytical, system science or modeling resources or tools which NIH should consider adding to the All of Us Researcher Workbench to leverage the data sets that will be generated by this study. In addition to the genetics, survey and electronic health records that All of Us already collects, new data sets are expected to include metagenomics, transcriptomics, metatranscriptomics, metabolomics, dietary information, meal chanllenge data, food images, health disparities, social and behavioral determinants of health, etc. [Respondents may suggest open source (e.g., AMON or QIIME2, DeepVariant) or commercial resources/tools].
4. Opportunities for the NIH to partner in achieving the goals of the Nutrition for Precision Health program with dot.org-s, dot.com-s or dot.edu-s (e.g., access to existing accessible data sets, platform developers). Comments on challenges and opportunities for engaging and collaborating with AI and machine learning researchers from math and engineering fields.
5. Any other topic the respondent feels is relevant for the NIH to consider in developing this strategic plan.

How to submit

Responses to this RFI must be submitted electronically to nutritionresearch@nih.gov. Responses must be received by 11:59 p.m. on Nov 15, 2020 Responses to this RFI are voluntary. Do not include any proprietary, classified, confidential, trade secret, or sensitive information in your response.

No forms are required for submission.

The responses will be reviewed by NIH staff, and individual feedback will not be provided to any responder. The Government will use the information submitted in response to this RFI at its discretion. The Government reserves the right to use any submitted information on public NIH websites, in reports, in summaries of the state of the science, in any possible resultant solicitation(s), grant(s), or cooperative agreement(s), or in the development of future funding opportunity announcements.

This RFI is for information and planning purposes only and shall not be construed as a solicitation, grant, or cooperative agreement, or as an obligation on the part of the Federal Government, the NIH, or individual NIH Institutes and Centers to provide support for any ideas identified in response to it. The Government will not pay for the preparation of any information submitted or for the Government’s use of such information. No basis for claims against the U.S. Government shall arise as a result of a response to this request for information or from the Government’s use of such information.

NIH looks forward to your input and we hope that you will share this RFI document with your colleagues.

Inquiries

Please direct all inquiries to:

Holly Nicastro, Ph.D., M.P.H.
Office of Nutrition Research
Telephone: 301-435-0383
Email: nutritionresearch@nih.gov

Christopher Lynch, Ph.D.
Office of Nutrition Research
Telephone: 301-827-3988
Email: nutritionresearch@nih.gov