Henry Memczak
Stanford University School of Medicine, USA
Title: Differentiation of Subtypes for Influenza Surveillance Using a Peptide-Based Detection Platform (FluType)
Biography
Biography: Henry Memczak
Abstract
The only cost-effective protection against influenza is vaccination. Due to rapid mutation continuously new subtypes appear, what requires annual reimmunization. For a correct vaccination recommendation, the circulating influenza strains have to be detected promptly and exactly and characterized regarding their antigenic properties. Due to recurring incidents of vaccine mismatches, there is a great need to speed up the process chain from identifying the right vaccine strains to their administration. The monitoring of subtypes as part of this process chain is carried out by national reference laboratories within the WHO Global Influenza Surveillance and Response System (GISRS). To this end, thousands of viruses from patient samples (e.g. throat smears) are isolated and analyzed each year. Currently this analysis involves complex and time-intensive (several weeks) animal experiments to produce specific hyperimmune sera in ferrets, which are necessary for the determination of the antigen profiles of circulating virus strains. These tests also bear difficulties in standardization and reproducibility, which restricts the significance of the results.
To replace this test a peptide-based assay for influenza virus subtyping is developed. The differentiation of the viruses takes place by a set of specifically designed peptidic recognition molecules which interact differently with the different influenza virus subtypes. The differentiation of influenza subtypes is performed by pattern recognition guided by machine learning algorithms, without any animal experiments.