SBIR/STTR Research Award

Software for sequencing human antibody proteins from polyclonal immune responses

Award identifier 9e29848e731e00499a85517c70b4c3cd217bde388cf0a56f36b9fb9b81315e4dAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,551,492

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2021

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
ABTERRA BIOSCIENCES, INC.
Proposal award date
2021-03-01
Contract end date
2023-02-28
UEI
TYHDLNB65NJ1
Solicitation number
PA19-272
Topic code
400

Research abstract

The natural immune response to foreign pathogens involves a complex coordination of cells, including an adaptive response to select and secrete antibodies into circulation. Individuals who have recovered from a pathogenic infection retain immune memory and continue to circulate pathogen-specific antibodies. For many infectious diseases like respiratory syncytial virus, Ebola, and poxviruses, antibodies with neutralizing activity to multiple viral strains have been discovered from human survivors. The discovered antibodies are highly valuable as potential biologic therapeutics for the broader population, as the antibodies have been naturally optimized to defend against human pathogens.Efforts to discover antibodies from humans recovering from coronavirus infection are underway, SARS-CoV-2 in particular, but are hampered by the limitations of existing antibody discovery platforms. Current approaches require screening for live B cells actively producing pathogen-specific antibodies, which are sensitive to cell death and rarely found in blood. In contrast, antibody protein is stable and pathogen-reactive antibodies are abundant in serum. While protein is the ideal material to start with, characterization of polyclonal antibody (pAb) protein presents new challenges.Recent advances in mass spectrometry and analysis have shown individual antibody candidates can be derived from affinity-purified pAb proteins when a sufficiently matched B-cell genetic antibody repertoire is provided. We aim to develop algorithms to supplant the need of a genetic antibody repertoire, and de novo identify antibody candidates from limited complexity pAb samples. This is achieved by improvements to de novo peptide sequencing using machine learning, and targeted assembly of specificity determining regions (CDR3s) and antibody frameworks using de Bruijn graphs. The proposed software will provide estimates of clonal diversity and candidate sequences that can be synthesized and tested for reactivity. In addition to addressing needs for infectious diseases, as demonstrated with an urgent unmet need to stop the COVID-19 pandemic, the software also applies to clinical and biomedical research needs in autoimmune disease, and commercial interests in replacing polyclonal antibody reagents with highly reproducible monoclonal antibody equivalents.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

12 SBIR/STTR records share this UEI (2012–2024). Reported award amounts total $9,838,077. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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