This chapter introduces the fundamental principles and therapeutic potential of mRNA-based cancer vaccines within the field of nanomedicine. It discusses the unique advantages of mRNA vaccines, emphasizing their potent immunogenicity, capacity to induce robust cellular and humoral immune responses, and establishment of lasting immune memory compared to traditional cancer therapies. Critical barriers, including mRNA instability, low intracellular delivery efficiency, and limited transfection efficacy, are identified. Special emphasis is placed on lipid nanoparticles (LNPs) as the primary delivery vectors capable of overcoming these barriers by protecting mRNA from enzymatic degradation and enhancing cellular uptake. The chapter highlights challenges in developing optimal LNP formulations, framing the central research problem around efficiently identifying nanocarriers that balance safety, efficacy, and transfection performance. The discussion sets a clear foundation for exploring machine learning-driven approaches to rationally design advanced LNP systems.

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An Introduction to mRNA Vaccines in Cancer Nanomedicine

  • Krish W. Ramadurai,
  • Abhirup Banerjee

摘要

This chapter introduces the fundamental principles and therapeutic potential of mRNA-based cancer vaccines within the field of nanomedicine. It discusses the unique advantages of mRNA vaccines, emphasizing their potent immunogenicity, capacity to induce robust cellular and humoral immune responses, and establishment of lasting immune memory compared to traditional cancer therapies. Critical barriers, including mRNA instability, low intracellular delivery efficiency, and limited transfection efficacy, are identified. Special emphasis is placed on lipid nanoparticles (LNPs) as the primary delivery vectors capable of overcoming these barriers by protecting mRNA from enzymatic degradation and enhancing cellular uptake. The chapter highlights challenges in developing optimal LNP formulations, framing the central research problem around efficiently identifying nanocarriers that balance safety, efficacy, and transfection performance. The discussion sets a clear foundation for exploring machine learning-driven approaches to rationally design advanced LNP systems.