If your research can aid in the development of software for data science in infectious and immune-mediated diseases research, consider applying to the notice of funding opportunity (NOFO): Development of Software for Data Science in Infectious and Immune-Mediated Diseases Research (U01, Clinical Trial Not Allowed).
The goal of this initiative is to develop data science software that improves acquisition, management, analysis, visualization, and dissemination for data science research on infectious and immune-mediated diseases (IID). IID research projects generate large, diverse, and complex data sets, including sequencing data, clinical data, immune phenotyping assay data, and imaging data. Relevant IID data science research could include computational methods to better understand disease mechanism, risk prediction, epidemiology, detection and diagnosis, treatment, and vaccines aligned with our research mission.
Research Objective
This NOFO supports software development for data science research in IID, based on existing data and algorithms. Additionally, this NOFO supports projects to develop or enhance existing software to accelerate and maximize data science research in IID. More importantly, the research software developed as part of this initiative will be able to integrate with the NIAID Data Ecosystem and be discoverable via robust meta data through the NIAID Data Ecosystem Data Discovery Portal.
We encourage applications focused on software for a broad range of data science methods, which may include, but are not limited to: data engineering and improving compliance with FAIR Guiding Principles, computer science technologies, algorithms and mathematics, methods to improve metadata, analysis of image data, clinical and epidemiological data, sequencing data, data visualizations and systems models to support a wide range of IID research.
Below are some examples of potential research software projects relevant to this NOFO:
- Data science approaches to mine, enhance, evaluate/identify linkages, integrate and (re)use data from electronic health records (EHR), clinical trial data, epidemiology, diagnostic, molecular or registry data.
- Generalizable tools and workflows for the integration of heterogenous data; approaches for data/metadata acquisition and annotation, processing, provenance, wrangling, standards, and data exchange formats for domain-specific data; validating and benchmarking or performance analysis.
- Community-based data models, automated metadata capture, and ontologies to facilitate data management, sharing, and reuse.
- Methods for secure federated learning, data visiting, and tabularization.
- Methods to improve the speed and accuracy of data analysis and re-analysis.
- Methods to conduct data disambiguation for de-identified linkage of data across networks including use of cryptographic methods.
- Advanced statistical and mathematical modeling methods, graph, and network theory approaches for predictive, interventional, and prognostic applications.
- Artificial intelligence or machine learning approaches for the detection and diagnosis, treatment planning, and medical decision support, predictive and personalized medicine for data analytics of high-throughput and multi-dimensional data.
- Intelligent text parsing/mining technologies (including Natural Language Processing) for biomedical data.
- Systems modeling that can address data or link models across scales or support the integration of multi-modal data.
Proposed projects must include activities that enable the software to be indexed in the NIAID Data Ecosystem Discovery Portal, including the exposure of metadata compliant with as many FAIR guiding principles as possible, preferably through the application programming interface (API). We encourage U01 recipients to use the metadata schema for computational tools used by the NIAID Data Ecosystem Discovery Portal.
NIAID will not consider any applications that propose the following areas of research and will not review them:
- Any project that does not result in re-usable software.
- Any project that generates new data, except for data collected about user experiences with the software.
- Projects that develop wet-lab technologies.
- Projects that produce only stand-alone source code or algorithms.
- Projects that do not include at least two letters of support from relevant researchers for whom the proposed software would benefit their field of study and how it would benefit them.
NIAID expects recipients to participate in workshops, working groups, and meetings for community interaction and cross-fertilization of methods and approaches. During meetings, recipients will report progress, seek new research directions and ideas, and update NIAID on issues of need. Recipients will also collaborate with NIAID to integrate the developed research software into the NIAID Data Ecosystem.
NIAID will play a central role in organizing for community interaction and cross-fertilization of methods and approaches.
Award and Deadline Information
NIAID intends to fund two or three awards. Annual direct costs are limited to $300,000. The scope of the proposed project should determine the project period, although the maximum project period is 3 years.
Applications are due on October 11, 2023, by 5 p.m. local time of the applicant organization.
Direct any inquiries about the NOFO to the Office of Data Science and Emerging Technologies (ODSET) at datascience-foa@niaid.nih.gov. For concerns related to peer review, contact Dr. Sandip Bhattacharyya at sandip.bhattacharyya@nih.gov or 240-278-7833.