Lost in Translation: Predicting Human Vaccine Response from Preclinical Animal Models
The recent increase in emergence of infectious diseases illuminates the need for more efficient vaccine development. Currently the pipeline is limited by our ability to relate biological findings from animal models to clinical trial outcomes. Here we propose a generalizable computational framework that enables us to predict vaccine efficacy in humans and identify correlates of immunity based on preclinical data. This cross-species model may improve our mechanistic understanding of vaccine-induced immunity and accelerate the development pipeline.