Opportunities & challenges of applying AI/ML to integrating systems vaccinology studies

Vaccines are essential tools in the control of infectious diseases. The development of vaccines has matured from a mostly empirical to a highly sophisticated approach that is science-grounded and based on state-of-the-art knowledge in molecular biology, immunology, and structural biology. Insights in the mechanism of action of vaccines have been driven by clinical research studies that leverage systems vaccinology approaches to unravel the links between the innate immune response and the quality and persistence of adaptive immunity. Over the last decade an increasing number of clinical systems vaccinology studies have been published. In parallel, developments in artificial intelligence and machine learning (AI/ML) have made a massive impact in real-life applications from image classification to speech recognition. AI/ML has also entered the world of vaccinology. In this manuscript, we reflect on how AI/ML could be used to leverage the wealth of clinical systems biology data to drive novel insights in vaccines mechanism of action.