PremiumScientists have developed an mRNA lipid nanoparticle vaccine containing antigens from all twenty known subtypes of influenza A and B viruses
Rodents to the rescue; Based on a study conducted by researchers from the US and Canada on mice and ferrets, they have created a vaccine made of mRNA lipid nanoparticles that contains antigens from each of the twenty known subtypes of influenza A and B viruses. This approach could be a path-breaking discovery as it could become the basis for future universal flu vaccines.
According to the study lead by Claudia Arevalo from University of Pennsylvania, the vaccine produced high levels of cross-reactive and subtype-specific antibodies in mice and ferrets and could shield animals from disease symptoms and demise following infection with both antigenically matched and mismatched influenza strains.
The study found that it is challenging to predict which flu strain will start the next flu pandemic, despite increased global surveillance, which emphasises the significance of a universal vaccine.
By including antigens unique to each subtype rather than just a smaller set of antigens shared by subtypes, the scientists' method differed from earlier attempts to create a universal flu vaccine, according to the study published in the journal Science.
Following the success of mRNA vaccines against SARS-CoV-2, researchers created 20 distinct nanoparticle encapsulated mRNAs, each of which encoded a different hemagglutinin antigen, a highly immunogenic flu protein that aids virus entry into cells, according to the study. Four months after vaccination, the mice's antibody levels remained largely stable.
According to the study, multivalent protein vaccines made using more conventional techniques elicited fewer antibodies and were less protective than the multivalent mRNA vaccine in the animals.
In early November, an early-stage study was announced by US pharmaceutical company Pfizer Inc. and its German partner BioNTech SE to assess a combination vaccine targeting COVID-19 and influenza.
(With inputs from PTI)