Application of Artificial Intelligence in the Design of Tumor mRNA Vaccines

Abstract

For many years, scientists have been focused on developing mRNA-based vaccines, an area that has transitioned from theoretical concepts to practical treatments in clinical settings. This remarkable progress highlights the speed at which scientific advancements can occur when collaboration and innovation intersect. mRNA vaccines offer several inherent advantages, such as robust immunogenicity, a lack of gene integration risks, and the potential for cost-effective production. However, challenges related to mRNA stability and degradation continue to pose significant hurdles. To address these challenges and enhance vaccine development, traditional trial-and-error methods are increasingly being complemented and, in some cases, replaced by rational design strategies that leverage artificial intelligence (AI). In this review, we explore the core technologies underpinning mRNA vaccines and discuss how AI-driven design methods are optimizing their development. We also present a case study of trRosettaRNA, a deep learning-based approach for automating the prediction of RNA three-dimensional structures. This method successfully predicts the 3D structure of target RNA, demonstrating the transformative potential of AI in optimizing vaccine design and further advancing mRNA-based therapeutic strategies.