Front Immunol

. 2023 Apr 6;14:1155880.
doi: 10.3389/fimmu.2023.1155880. eCollection 2023.
H3N2 influenza hemagglutination inhibition method qualification with data driven statistical methods for human clinical trials

Sheetal Sawant 1 2 3 , Sarah Anne Gurley 1 2 3 , R Glenn Overman 1 2 3 , Angelina Sharak 1 2 3 , Sarah V Mudrak 1 2 3 , Thomas Oguin 3rd 2 , Gregory D Sempowski 2 , Marcella Sarzotti-Kelsoe 1 2 3 , Emmanuel B Walter 2 4 5 , Hang Xie 6 , Marcela F Pasetti 7 8 , M Anthony Moody 2 3 4 , Georgia D Tomaras 1 2 3 5

AffiliationsFree PMC article


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.

Keywords: antibody; clinical trials; data pipeline; hemagglutination inhibition (HAI); human; influenza; qualification; statistical analysis.