Systems vaccinology and big data in the vaccine development chain

Raeven, René H. M.; van Riet, Elly; Meiring, Hugo D.; Metz, Bernard; Kersten, Gideon F. A.

Systems vaccinology has been implemented in the different phases of the vaccine development chain and has become a relevant approach in the field of vaccinology. The recent progression in systems vaccinology has led to successful initiatives such as the ADITEC project 134 that provided a novel gene expression method to analyze biomarkers of tuberculosis pathogenesis 135 as well as a study where safety and immunogenicity of a novel vaccine against tuberculosis (VPM1002) were evaluated. 136 To achieve maximum vaccine efficacy and safety, future vaccine research will have to focus on target groups such as neonates 137, 138 or even on the development of personalized vaccines. 139 Systems vaccinology approaches can be further applied to investigate the inter-group differences in vaccine responsiveness between healthy adults and specific target groups such as infants, and elderly or immune-deficient individuals. 140 Investigating vaccine-induced responses with systems vaccinology has led to a trend of gathering massive amounts of data going as deep as investigating every molecule in single cells. Acquiring large data sets is far easier than extracting novel relevant information from those data. Furthermore, the amount of data is constantly increasing, especially when combining data sets of different origin (genes versus proteins versus cells). This requires equally advanced tools for (i) data visualization and (ii) translation of content to knowledge and understanding, forcing a dialogue between vaccine developers and bioinformatics experts. In the future, implementation of artificial intelligence could assist in data processing and for data visualization online publications may become interactive allowing readers to scroll through, for example, the immune responses induced by immunization over time.