Abstract
RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testing has provided some key insights on how RNA vaccines interact with the innate immune system, their mechanism of action appears to be fragmented amid the literature, making it difficult to formulate new hypotheses to be tested in clinical settings and ultimately improve this technology platform. Here, we propose a systems biology approach, based on the combination of literature mining and mechanistic graphical modeling, to consolidate existing knowledge around mRNA vaccines mode of action and enhance the translatability of preclinical hypotheses into clinical evidence. A Natural Language Processing (NLP) pipeline for automated knowledge extraction retrieved key biological evidences that were joined into an interactive mechanistic graphical model representing the chain of immune events induced by mRNA vaccines administration. The achieved mechanistic graphical model will help the design of future experiments, foster the generation of new hypotheses and set the basis for the development of mathematical models capable of simulating and predicting the immune response to mRNA vaccines.
Highlights
Since December 2019 SARS-CoV-2 virus has spread across the globe, becoming a pandemic threat and claiming millions of lives
MRNA Vaccine Platforms Improvement vaccines represent an important advancement in the history of vaccinology to defeat infectious diseases. messenger RNA (mRNA) vaccines are based on the concept that, starting from the amino acid sequence of the antigen of interest, it is possible to design a related mRNA sequence that is employed by the cells of the body as template to express the antigen in situ. mRNA vaccines are known to stimulate both arms of the humoral and cellular immunity [7], their mechanism of action is still partially understood
Several pharmaceutical companies and research institutes are working at the development of new platforms for mRNA-based antigen delivery, trying to identify and characterize those parameters that are required for a safe and protective vaccine response
Summary
Since December 2019 SARS-CoV-2 virus has spread across the globe, becoming a pandemic threat and claiming millions of lives. The first two vaccines that received emergency use authorization by EMA and FDA to prevent COVID-19 disease in humans are based on messenger RNA (mRNA), a relatively new vaccine platform with several advantages over more traditional approaches for vaccine design [1,2,3,4,5,6,7] Because of their unique features in terms of manufacturability, mechanism of action and ability to induce potent immune responses, mRNA. The generated knowledge tends to be rather specific to each individual platform, not always generalizable and sometimes even fragmented This is what motivated our effort to collect and consolidate all publicly available scientific evidences, related to mRNA vaccine mode of action, into an interactive mechanistic graphical model (Figure 2, link to https://www.cosbi.eu/fx/9839203 dynamic figure) tracing the stages of the immune response to mRNA vaccines, from the innate immune activation at the site of injection up to the adaptive response, measurable in the peripheral blood system several days after vaccination. The proposed mechanistic graphical model facilitates the interpretation of what has been discovered so far and fosters interactions among investigators with very different backgrounds, such as immunologists and data scientists
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