# i-AKC: Integrated AIRR Knowledge Commons

> **NIH NIH U24** · UT SOUTHWESTERN MEDICAL CENTER · 2024 · $994,460

## Abstract

PROJECT SUMMARY/ABSTRACT:
Immune receptors of the adaptive immune system (antibody/B-cell or T-cell receptors, or AIRR data) are
designed to recognize and remove pathogens, and also recognize and preserve self-molecules. Therefore, these
receptors have to be highly variable; it has been estimated that the number of possible human B-cell receptors
approaches 1013. In addition to the diversity of these receptor sequences, the genes that underlie the production
of these receptor molecules are highly diverse and complicated, and the data describing how these receptors
bind to antigens (such as influenza) are also highly complex. Repositories to curate, analyze, and share these
data are necessary to characterize B/T cell function in disease, as well as facilitate the discovery of new vaccine
leads and therapeutic monoclonal antibodies to suppress autoimmune disease and cancer. Such data
repositories are available, but they tend to focus on only one aspect of the data. Given that these repositories
typically have been developed independently, the primary data and associated metadata (age, demography,
sex, etc.) of the samples are stored in non-compatible forms, and in addition, the enormous size and complexity
of the data make data sharing and integrated analyses extremely challenging. The goal of the proposed research
is to establish the integrated AIRR Knowledge Commons (i-AKC), a novel knowledgebase that will allow
seamless access, exploration, analysis, querying, and downloading of these various data types from a single
point of entry. Our approach will be based on the very successful AIRR Community initiative, a group of
immunologists, bioinformaticians, and experts in ethics and data sharing who have worked together since 2015
to develop protocols and standards for analysis and data sharing tools. One of the outcomes of the AIRR
Community is the AIRR Data Commons, a set of data repositories that store the immense immune receptor
repertoires that underlie the adaptive immune response. The proposed research takes the next important step
of integrating (1) the AIRR Data Commons with repositories of (2) antigen/receptor binding and (3) germline
immune genes. Steps to producing the i-AKC are (1) develop a common data model and establish common data
elements relying on existing ontologies and community standards, (2) integrate the data using innovative
algorithms and automation tools and enrich it with new knowledge derived from algorithms operating on the
integrated data, and (3) community building. Using the i-AKC, researchers will, for example, be able to discover
receptor sequences based on metadata or sequence searches, seamlessly examine information on the germline
genes underlying these receptor sequences or examine what is known about the binding targets of these
receptors. This novel and innovative knowledgebase will facilitate data and knowledge exploration that would be
prohibitively difficult using sets of “siloed” repositories and will gre...

## Key facts

- **NIH application ID:** 10896326
- **Project number:** 5U24AI177622-02
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** LINDSAY G. COWELL
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $994,460
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10896326

## Citation

> US National Institutes of Health, RePORTER application 10896326, i-AKC: Integrated AIRR Knowledge Commons (5U24AI177622-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10896326. Licensed CC0.

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