The continued advance of vaccine adjuvants - 'we can work it out'.

In the last decade there have been some significant advances in vaccine adjuvants, particularly in relation to their inclusion in licensed products. This was proceeded by several decades in which such advances were very scarce, or entirely absent, but several novel adjuvants have now been included in licensed products, including in the US. These advances have relied upon several key technological insights that have emerged in this time period, which have finally allowed an in depth understanding of how adjuvants work. These advances include developments in systems biology approaches which allow the hypotheses first advanced in pre-clinical studies to be critically evaluated in human studies. This review highlights these recent advances, both in relation to the adjuvants themselves, but also the technologies that have enabled their successes. Moreover, we critically appraise what will come next, both in terms of new adjuvant molecules, and the technologies needed to allow them to succeed. We confidently predict that additional adjuvants will emerge in the coming years that will reach approval in licensed products, but that the components might differ significantly from those which are currently used. Gradually, the natural products that were originally used to build adjuvants, since they were readily available at the time of initial development, will come to be replaced by synthetic or biosynthetic materials, with more appealing attributes, including more reliable and robust supply, along with reduced heterogeneity. The recent advance in vaccine adjuvants is timely, given the need to create novel vaccines to deal with the COVID-19 pandemic. Although, we must ensure that the rigorous safety evaluations that allowed the current adjuvants to advance are not 'short-changed' in the push for new vaccines to meet the global challenge as quickly as possible, we must not jeopardize what we have achieved, by pushing less established technologies too quickly, if the data does not fully support it.