Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy

Front Cell Infect Microbiol. 2025 Jan 20:14:1501010. doi: 10.3389/fcimb.2024.1501010. eCollection 2024.

Abstract

Messenger RNA (mRNA) vaccines offer an adaptable and scalable platform for cancer immunotherapy, requiring optimal design to elicit a robust and targeted immune response. Recent advancements in bioinformatics and artificial intelligence (AI) have significantly enhanced the design, prediction, and optimization of mRNA vaccines. This paper reviews technologies that streamline mRNA vaccine development, from genomic sequencing to lipid nanoparticle (LNP) formulation. We discuss how accurate predictions of neoantigen structures guide the design of mRNA sequences that effectively target immune and cancer cells. Furthermore, we examine AI-driven approaches that optimize mRNA-LNP formulations, enhancing delivery and stability. These technological innovations not only improve vaccine design but also enhance pharmacokinetics and pharmacodynamics, offering promising avenues for personalized cancer immunotherapy.

Keywords: artificial intelligence; bioinformatics; lipid nanoparticles; neo-antigen mRNA vaccines; targeted immunotherapy.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence*
  • Cancer Vaccines* / genetics
  • Cancer Vaccines* / immunology
  • Computational Biology* / methods
  • Humans
  • Immunotherapy* / methods
  • Nanoparticles / chemistry
  • Neoplasms* / immunology
  • Neoplasms* / therapy
  • RNA, Messenger / genetics
  • Vaccine Development
  • Vaccines, Synthetic / administration & dosage
  • Vaccines, Synthetic / genetics
  • Vaccines, Synthetic / immunology
  • mRNA Vaccines*

Substances

  • Cancer Vaccines
  • mRNA Vaccines
  • RNA, Messenger
  • Vaccines, Synthetic

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was financially supported by Zhejiang Shuren University Basic Scientific Research Special Funds (2024XZ011). This funder did not participate in the designing, performing, or reporting of the current study.