{"doi":"10.3389/fimmu.2023.1155880","title":"H3N2 influenza hemagglutination inhibition method qualification with data driven statistical methods for human clinical trials","abstract":"Introduction: Hemagglutination inhibition (HAI) antibody titers to seasonal influenza strains are important surrogates for vaccine-elicited protection. However, HAI assays can be variable across labs, with low sensitivity across diverse viruses due to lack of standardization. Performing qualification of these assays on a strain specific level enables the precise and accurate quantification of HAI titers. Influenza A (H3N2) continues to be a predominant circulating subtype in most countries in Europe and North America since 1968 and is thus a focus of influenza vaccine research. Methods: As a part of the National Institutes of Health (NIH)-funded Collaborative Influenza Vaccine Innovation Centers (CIVICs) program, we report on the identification of a robust assay design, rigorous statistical analysis, and complete qualification of an HAI assay using A/Texas/71/2017 as a representative H3N2 strain and guinea pig red blood cells and neuraminidase (NA) inhibitor oseltamivir to prevent NA-mediated agglutination. Results: This qualified HAI assay is precise (calculated by the geometric coefficient of variation (GCV)) for intermediate precision and intra-operator variability, accurate calculated by relative error, perfectly linear (slope of -1, R-Square 1), robust (<25% GCV) and depicts high specificity and sensitivity. This HAI method was successfully qualified for another H3N2 influenza strain A/Singapore/INFIMH-16-0019/2016, meeting all pre-specified acceptance criteria. Discussion: These results demonstrate that HAI qualification and data generation for new influenza strains can be achieved efficiently with minimal extra testing and development. We report on a qualified and adaptable influenza serology method and analysis strategy to measure quantifiable HAI titers to define correlates of vaccine mediated protection in human clinical trials.","journal":"Frontiers in Immunology","year":2023,"id":360464,"datarank":0.3453877639491069,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.0,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9615,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1112282,"name":"Sarah Anne Gurley","orcid":null,"position":1,"is_corresponding":false},{"id":596828,"name":"R. Glenn Overman","orcid":null,"position":2,"is_corresponding":false},{"id":1112283,"name":"Angelina Sharak","orcid":null,"position":3,"is_corresponding":false},{"id":722429,"name":"Sarah V. Mudrak","orcid":null,"position":4,"is_corresponding":false},{"id":230173,"name":"Thomas H. Oguin","orcid":"0000-0001-8959-4025","position":5,"is_corresponding":false},{"id":225651,"name":"Gregory D. Sempowski","orcid":"0000-0003-0391-6594","position":6,"is_corresponding":false},{"id":475191,"name":"Marcella Sarzotti‐Kelsoe","orcid":"0000-0001-7392-6072","position":7,"is_corresponding":false},{"id":325734,"name":"Emmanuel B. Walter","orcid":"0000-0001-6502-6736","position":8,"is_corresponding":false},{"id":388746,"name":"Hang Xie","orcid":"0000-0001-8318-5554","position":9,"is_corresponding":false},{"id":299790,"name":"Marcela F. Pasetti","orcid":"0000-0003-0894-4009","position":10,"is_corresponding":false},{"id":32982,"name":"M. Anthony Moody","orcid":null,"position":11,"is_corresponding":false},{"id":258351,"name":"Georgia D. Tomaras","orcid":"0000-0001-8076-1931","position":12,"is_corresponding":false},{"id":258348,"name":"Sheetal Sawant","orcid":"0000-0002-1109-7907","position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:14:01.896928Z","pmid":"37090729","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}