An imidazole modified lipid confers enhanced mRNA-LNP stability and strong immunization properties in mice and non-human primates.

The mRNA vaccine technology has promising applications to fight infectious diseases as demonstrated by the licensing of two mRNA-based vaccines, Comirnaty® (Pfizer/BioNtech) and Spikevax® (Moderna), in the context of the Covid-19 crisis. Safe and effective delivery systems are essential to the performance of these vaccines and lipid nanoparticles (LNPs) able to entrap, protect and deliver the mRNA in vivo are considered by many as the current "best in class". Nevertheless, current mRNA/LNP vaccine technology has still some limitations, one of them being thermostability, as evidenced by the ultracold distribution chain required for the licensed vaccines. We found that the thermostability of mRNA/LNP, could be improved by a novel imidazole modified lipid, DOG-IM4, in combination with standard helper lipids. DOG-IM4 comprises an ionizable head group consisting of imidazole, a dioleoyl lipid tail and a short flexible polyoxyethylene spacer between the head and tail. Here we describe the synthesis of DOG-IM4 and show that DOG-IM4 LNPs confer strong immunization properties to influenza HA mRNA in mice and macaques and a remarkable stability to the encapsulated mRNA when stored liquid in phosphate buffered saline at 4 °C. We speculate the increased stability to result from some specific attributes of the lipid's imidazole head group.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines.

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.