NIAID has awarded grants to three research teams for the development of software that advances infectious and immune-mediated disease (IID) research. The three funded projects will develop software that improves the acquisition, management, analysis, visualization, and dissemination of IID data.
There is a need for easy-to-use software to enable new computational algorithms, tools, or technologies to advance biomedical research and support reproducibility and data reuse. Data access and reuse, a key strategic priority for NIAID, can lead to the discovery of new knowledge; improve our understanding of mechanisms of transmission, infection, immune response, and pathogenesis; and help us develop new and improved diagnostics, therapeutics, and vaccines.
These recent awards, focused on different scientific domains, will each develop methods and tools that provide insights into important research questions and create frameworks that can extend to the broader biomedical community. For example, one of the grant recipients, Dajiang Liu, Ph.D., M.A., of Pennsylvania State University, said that the grant will allow his team to develop new tools for discovery and clinical translations in autoimmune diseases.
"AI and data science have transformed biomedical research in autoimmune diseases,” Dr. Liu said. “With massive and complex datasets from electronic health record-based biobanks and multi-omics studies, the field desperately needs tools to translate big data into knowledge."
Software projects at various stages of maturity were considered, ranging from early-stage prototyping to software in later stages of development.
The NIAID-funded projects will result in software products that are easily accessible by the IID research community — either by being installed locally or through an online interface. The software will be developed and distributed consistent with community standards for reuse and interoperability. Software products must also use FAIR (Findable, Accessible, Interoperable, Reusable) metadata so that they can be found using the NIAID Data Ecosystem Discovery Portal.
The funding opportunity was administered by the NIAID Office of Data Science and Emerging Technologies (ODSET). It posted in June 2023 and closed the following October.
Every seven years, the National Institutes of Health (NIH) re-evaluates and competitively renews its funding for the HIV clinical research networks operating in the United States and internationally. These pages represent the previous consultations and network competitions that led to awards in 2020:
The National Institute of Allergy and Infectious Diseases (NIAID) is funding new research related to computational modeling systems of infection and immunity.
The Notice of Special Interest (NOSI), NOT-AI-24-060, is titled “Systems Modeling of Infection and Immunity Across Biological Scales” and was released on July 23. The NOSI encourages researchers to submit applications through the R01 and R21parent announcements focused on research activities relevant to systems modeling of infection and immunity.
Computational modeling holds tremendous potential for infectious and immune-mediated disease (IID) research. Modeling helps us to elucidate biological mechanisms of infection and transmission, understand immune system responses to various triggers, and characterize longitudinal trajectories of allergic or immune-mediated diseases. Models can also predict population-level epidemic trajectories and optimize public health control measures and therapeutic interventions in response to epidemic threats.
Grant applications citing this NOSI will be reviewed through the established process through the Center for Scientific Review (CSR) and will use NIAID paylines. Projects that include innovative modeling research addressing key NIAID priority biomedical questions across biological scales will be considered for funding. These projects may include, but are not limited to, modeling the infection process, modeling immune and allergenic responses, population-level modeling, and mechanistic models of vaccines and therapeutics. Read the full NOSI to find a list of suggested modeling research topics.
Working With the Center of Excellence
Grant recipients are expected to work collaboratively with NIAID’s Center of Excellence (CoE) for Systems Modeling of Infection and Immunity across Biological Scales, scheduled to initiate in 2025. The CoE will play an important role: Working alongside NIAID, the CoE will coordinate the research community of IID computational modelers and advance IID modeling research across biological scales. This coordinating body aims to accelerate multi-scale model development, sharing, and re-use, to the benefit of the entire IID research community.
Recipients will also be expected to collaborate with the diverse community of investigators participating in the CoE. This includes sharing models and modeling methods in a reproducible way aligned with the Findable, Accessible, Interoperable, and Reusable (FAIR) principles and the NIAID Data Ecosystem. The CoE aims to foster collaboration among grant recipients through community-building activities, such as an annual meeting, workshops, educational opportunities, and Opportunity Funds.
The first available due date for applications is October 5, 2024. Interested parties can submit applications using one of the following notices of funding opportunities (NOFOs) or any reissues of these announcements through the expiration date of this notice:
PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)
PA-20-195 - NIH Exploratory/Developmental Research Grant Program (Parent R21 Clinical Trial Not Allowed)
All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:
To acknowledge this NOSI, applicants should include “NOT-AI-24-060” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form.
In the “Research Strategy,” include an additional section titled "Collaborative Activities" that describes plans for collaboration and participation in activities organized by the CoE for Systems Modeling of Infection and Immunity across Biological Scales. Discuss how these plans will support and enhance the utility and/or interoperability of modeling research proposed in response to this Notice.
How to Access NIAID’s Preclinical Services for Your Product Development Program
Learn how to access one of NIAID's free preclinical services (PCS) through the suite of service contracts that support the development of therapeutics, vaccines, and diagnostics. Investigators in academia, a nonprofit organization, industry, or government in the United States or worldwide can request PCS. You need not be a grantee of NIAID or another NIH Institute or Center.
Preclinical Product Development Services for Infectious Disease Research
The Division of Microbiology and Infectious Diseases (DMID) has built a comprehensive set of preclinical services to facilitate efforts to develop the next generation of vaccines, diagnostics and therapeutics for a broad array of bacterial, viral, fungal and parasitic pathogens, as well as novel control approaches for invertebrate vectors of public health importance. Through these in-kind services, eligible investigators worldwide get access to expertise, research materials, and state-of-the-art technologies at minimal or no charge.
Read about the steps you need to take to access NIAID’s preclinical services for your product development program.
Information about available services, eligibility, product evaluation criteria, and the request process are unique to each program. DMID scientific contacts are listed for each resource and are available to answer questions and provide further guidance about access to these resources.
In Vitro Assessments of Antimicrobial Activity. These services evaluate promising candidate countermeasures in vitro for antimicrobial activity against microbial pathogens and vectors, including clinical isolates.
Preclinical Models of Infectious Diseases. These services support (1) the development and refinement of animal models and animal replacement technologies and (2) provide testing in animal models and human microphysiological systems (against priority viruses only) including organ-on-a-chip and organoid-based infection models for promising candidate countermeasures.
Therapeutic Development Services. These services support the testing and manufacturing of therapeutic agents for infectious diseases, such as small molecules, peptides, monoclonal antibodies, recombinant proteins, and nucleic acid-based vectors (siRNA, plasmids). Services include chemistry and manufacturing, and preclinical safety and pharmacokinetic studies for IND packages (such as ADMET, off-target toxicity profiling, and MTD studies).
Vaccine Development Services. These services support the testing and manufacturing of vaccines intended for use in the investigation, control, prevention, and treatment of a wide range of infectious agents.
Diagnostics Development Services. These services offer reagents, platform testing, and planning and design support to accelerate product development of in vitro diagnostics for infectious diseases, from research feasibility through clinical validation.
Additional Resources for Early Preclinical Development
The following resources may have different access processes than the core preclinical services listed above. Please refer to the links below for more information:
Antibacterial Resistance Leadership Group (ARLG) Biorepository
The Antibacterial Resistance Leadership Group (ARLG) Laboratory Center manages a biorepository of bacterial clinical study isolates that are available upon request to investigators. The ARLG Biorepository Strain Catalogue can be used to search for available isolates.
BEI Resources
BEI Resources Repository supplies organisms and reagents to the broad community of microbiology and infectious diseases researchers. Investigators can access materials directly through an online catalog. There is no charge for research materials, but domestic investigators will be required to pay for shipping costs. BEI Resources also encourages and supports the deposit of materials from researchers and institutions.
Bioinformatics Resource Centers (BRCs)
The NIAID Bioinformatics Resource Centers (BRCs) provide data-driven, production-level, sustainable computational platforms to enable sharing, accessing, and analyzing data with various analytical tools and educational materials that support interoperability for the infectious diseases research community.
Centers for Research on Structural Biology of Infectious Diseases (CRSTAL-ID)
The NIAID Centers for Structural Biology of Infectious Diseases (CRSTAL-IDs) characterize the 3D structure of proteins from bacterial, viral, and eukaryotic pathogens using state-of-the-art technologies from computational modeling, x-ray crystallography, NMR and CryoEM. The CRSTAL-IDs additionally have the capacity for supporting the discovery of therapeutics and vaccines using structural-guided design and high throughput chemical screening platforms. Investigators can contact the CRSTAL-ID centers directly to access expert services and to request determinations of protein structures.
Chemistry Center for Combating Antibacterial Resistant Bacteria
The Chemistry Center for Combating Antibacterial Resistant Bacteria (CC4CARB) is an innovative chemistry center focused on the synthesis, acquisition, and distribution of rationally designed, focused libraries for use in Gram-negative antibacterial drug discovery programs at no cost to the global scientific community. The ultimate objective of CC4CARB is to create a large collection of chemical matter specifically targeting Gram-negative antimicrobial drug discovery. Investigators may submit their scaffold proposals for chemical synthesis directly to the CC4CARB website.
Dataset of NCI’s Natural Product Library Screen for Antimicrobial Activity
In collaboration with the National Cancer Institute's (NCI) Program for Natural Product Discovery (NPNPD), NIAID screened one of the largest publicly available collections of natural products against three bacterial and one fungal species. A publication on the screening process and results can be found on PubMed. The screening dataset and instructions for contacting NCI’s Natural Products Branch to acquire natural product libraries or extracts of interest can be found on the NCI wiki.
World Reference Center for Emerging Viruses and Arboviruses (WRCEVA)
The World Reference Center for Emerging Viruses and Arboviruses (WRCEVA) program maintains the Emerging Viruses and Arboviruses Reference Collection and provides reagents and support for investigations of virus outbreaks throughout the world.
Contact Your Program Officer To Discuss Scientific Services
Rapid data sharing is essential for advancing research on infectious and immune-mediated diseases. NIAID supports broad sharing of research data, while protecting the privacy of human research participants. Read on to learn how to navigate data sharing policies at NIAID and the National Institutes of Health.
NIH issued the Data Management and Sharing (DMS) policy to promote the sharing of scientific data. Effective as of January 25, 2023, the DMS policy sets expectations for planning and budgeting for data management and sharing, submitting a DMS Plan when applying for funding, and implementing the DMS Plan throughout your research.
Genomic data is a critical shared resource and valuable tool for research that benefits the scientific community. To facilitate the translation of research results into applications that improve human health, NIH expects institutions and researchers to broadly and responsibly share genomic data generated by NIH funds.
Along with the GDS and DMS policies, NIH has sharing policies addressing topics from model organisms to publications. NIH offers an online tool to help researchers determine which NIH data sharing policies apply to their research.
Guidance for NIAID Researchers
What data types should be shared?
NIAID expects sharing of data and metadata associated with funded research using common data standards, if possible. Any ethical, legal, and/or technical factors that may affect sharing can be detailed in the Data Management and Sharing (DMS) Plan. Data types may include, but are not limited to, genomic, transcriptomic, imaging, proteomics, metabolomics, immunological, flow cytometry, protein structures, and clinical data from human research participants generated during research projects and/or clinical trials.
The DMS policy requires sharing of all scientific data, defined as all data necessary to replicate research findings regardless of whether the data are used to support scientific papers. For example, for clinical trials, this includes data for primary, secondary, and additional endpoints. However, not all data must be shared, including data resulting from calibration or preliminary analyses. See NIH guidance for additional details.
Metadata is additional labeling of your data. This “data about data” describes data contents and structure and makes research data “discoverable” by linking it to publications and funding information. Applying metadata allows other researchers to interpret and reuse your data and prevents misuse, misinterpretation, and confusion.
The exact metadata or other associated documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset. Metadata or other information associated with research data may include the methodology and procedures used to collect the data, data labels, definitions of variables, and any other information necessary to reproduce and understand the data.
Example Metadata Fields
Authors(s), Citation, Dataset Name, Date Modified, Date Published, Description, Experimental Host, Funder Number, Grant Number, Measurement, Pathogen, Publisher, Source Code, Technique, Variable(s) Measured
Where do I share data from NIAID-funded or conducted research?
NIAID encourages the use of established domain-specific repositories for data sharing to support effective data discovery, access, and reuse. To select a repository for sharing data, review the list of NIH-Supported Data Sharing Resources, including NIAID-preferred repositories. When domain-specific repositories are not available, NIAID encourages researchers to share data via widely used generalist repositories. Read more about selecting a data repository.
It is common practice for researchers to share data as supplementary material to journal articles. However, making data available solely through publications, supplemental material, etc. is not compliant with the NIH DMS policy.
When do I share data from NIAID-funded or conducted research?
The NIH DMS policy requires data sharing at the time of publication or at the end of the performance period, whichever comes first. NIAID strongly encourages scientific data to be shared as rapidly as possible. All scientific data generated by a study, including data beyond that used to support a publication, should be shared before the end of the performance period.
Human and non-human genomic data subject to the Genomic Data Sharing (GDS) policy must still comply with the GDS policy timeline expectations for data submission and sharing. To determine if your research is subject to the GDS policy, please review when the GDS policy applies.
In some instances, data sharing before publication or the end of the performance period may be warranted, such as during public health emergencies. See NIH guidance for details on data submission and sharing timelines.
How do I develop a DMS Plan?
Under the DMS policy, NIH expects investigators and institutions to:
Prepare a DMS Plan and budget for managing and sharing scientific data.
Submit a DMS Plan when applying for funding.
Comply with the approved DMS Plan.
Before you apply for NIAID funding, determine if your application falls under the DMS policy using resources available on Research Covered by the 2023 DMS policy. If your application is subject to the Genomic Data Sharing policy, your DMS Plan should address genomic data considerations.
Are there any NIAID-specific data sharing policies?
All NIAID researchers should comply with the NIH DMS policy and other relevant NIH policies. Check the notice of funding opportunity and review institute- and center-specific data sharing policies to determine if you should consider additional data sharing requirements.
Carrying Out a Data Management and Sharing Plan? Take Note of These Updates
The following resources can help NIAID researchers with data sharing and access in controlled-access, NIH-supported repositories.
Genomic Program Administrators (GPAs)
The NIAID Genomic Program Administrators (GPAs) assist investigators with study registration and data submission to controlled-access repositories, such as dbGaP, and serve as experts on the Genomic Data Sharing (GDS) policy for NIAID. Divisional GPAs provide support to investigators funded by or within the NIAID divisions, with assistance from the overall NIAID GPA in the Office of Data Science and Emerging Technologies.
Principal Investigators should direct questions related to data management, sharing, and policies to their Program Officers (POs). Questions from POs on these topics should be directed to their divisional GPA or the overall NIAID GPA (niaid_datasharing@niaid.nih.gov).
We encourage controlled access data repositories that host NIAID data to use the NIAID DAC for review of their Data Access Requests. Please contact niaid_datasharing@niaid.nih.gov with any questions about the NIAID DAC.
Apply for a Grant: Learn more about applying for funding with this step-by-step guide.
External Resources
NIAID cannot attest to the accuracy of a non-federal site. Linking to a non-federal site does not constitute an endorsement by NIH or any of its employees of the sponsors or the information and products presented on the site.
DMPTool: This tool can help researchers create data management plans (DMPs), including NIH-GEN DMSP.
Data Science Across NIAID
Researchers across NIAID use data science to accelerate research into understanding, treating, and preventing infectious, immunologic, and allergic diseases. Learn more about data science research at each of the offices and centers listed below.
Bioinformatics and Computational Biosciences Branch
The Office of Cyber Infrastructure and Computational Biology (OCICB) Bioinformatics and Computational Biosciences Branch (BCBB) serves as a centralized resource for data science and emerging technologies. BCBB utilizes cutting-edge techniques like machine learning and network analysis to support, enable, and advance biomedical discovery for NIAID researchers and collaborators.
The Research Technologies Branch (RTB) Integrated Data Sciences Section (IDSS) provides scientific consultation, training and workshops, computational and data science support, and technology collaboration. IDSS works with NIAID investigators to provide bioinformatics, data science, and computational biology expertise at all project stages, from experimental design through manuscript preparation.
The Office of Biostatistics Research (OBR) provides statistical support to NIAID intramural and extramural programs. OBR oversees the Biostatistics Research Branch, the Clinical Trials Research and Statistics Branch, and the Mathematical Biology Section. Together these groups engage in collaborative research with NIAID scientists, develop new statistical methods and mathematical models, coordinate biostatistics grants, and provide statistical oversight in research design.
The Office of Data Science and Emerging Technologies (ODSET) coordinates the development and implementation of NIAID’s data science strategy across its entire global portfolio of research and training programs. The overall goal of the office is to enable the efficient use of data and computational methods to better understand, treat, and ultimately prevent infectious, immunologic, and allergic diseases.
Advanced technologies research fields, such as genomics, proteomics, and bioinformatics, hold great promise for developing new diagnostics, therapeutics, and vaccines to treat and prevent infectious and immune-mediated diseases. Sophisticated tools are being used to determine the genetic make-up of disease-causing pathogens, to analyze discrepancies among pathogen strains, and to evaluate how immune system responses differ.
NIAID is a leader in the field of bioinformatics and our work is growing and expanding as technologies advance. NIAID supported contracts combined with internally developed technologies offer services related to bioinformatics.
NIAID has multiple funding opportunities currently open to support new data science research, training, and technology development to better understand, treat, and ultimately prevent infectious, immunologic, and allergic diseases. The list below is coordinated by the Office of Data Science and Emerging Technologies (ODSET). Funding opportunities from across NIAID will be added on an ongoing basis.
The purpose of this Notice is to announce the collaboration between the NIH and the National Science Foundation (NSF) on an interagency funding opportunity, NSF-23-614, Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science. The Smart Health program supports innovative, high-risk/high-reward research with the promise of disruptive transformations in biomedical and public health research.
Notice Number: NOT-OD-23-165 Posting Date: August 28, 2023 Expiration Date:
This notice announces the availability of funds from the Office of Data Science Strategy (ODSS) to NIH-managed or NIH-majority-funded projects that may benefit from using the cloud. The purpose of this announcement is to explore and test potential opportunities for leveraging cloud solutions to enhance existing NIH activities. Projects already using cloud may apply to explore and test cloud capabilities not yet leveraged.
Notice Number: NOT-OD-24-078 Posting Date: March 27, 2024 Expiration Date: June 19, 2026
NIAID Research Career Development Awards
K01: Mentored Research Scientist Development Award
Qualified applicants must have a research or health-professional doctoral degree and research must focus on epidemiology and/or data science. Per K01 guidelines in the 2019 Guide notice (NOT-Al-19-061), "This includes but is not limited to computational modeling, bioinformatics, big data and advanced statistical analyses in the prevention, treatment, discovery, prediction or forecasting of infectious, immunologic and/or allergic diseases." Search for NIAID K01 Funding Opportunities to get a current list.
K25: Mentored Quantitative Research Development Award
Qualified applicants must have an advanced doctoral degree in a quantitative science field and must be at a postdoctoral to senior faculty level. Additionally, they must demonstrate productivity in their field and must demonstrate intentions to expand their research such that their contributions to behavioral, biomedical, bioimaging, or bioengineering research will increase. Note that there may be restrictions based on past NIH funding - details can be found in the parent K25 notice of funding opportunity.
More NIH Funding Opportunities
NIH Data Science Funding
The query linked below, developed by the NIH Office of Data Science Strategy (ODSS), shows a list of data science and related funding opportunities on the NIH Grants and Funding website.
The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) curates data science funding opportunities from NCI and across the NIH.
The NIH Common Fund supports research spanning NIH research domains.Explore the list of current programs to find active or future funding opportunities indicated on each project’s page.
