Artificial intelligence in vaccine development: applications, implementation, and future directions

Area of Science:

• Biomedical Sciences
• Immunology
• Computational Biology

Background:

• Vaccination is a critical medical intervention saving numerous lives.
• Conventional vaccine development is lengthy, costly, and has high failure rates.
• There is a need for more efficient and systematic vaccine development approaches.

Purpose of the Study:

• To review the current applications of artificial intelligence (AI) in vaccine development.
• To highlight recent advancements and translational challenges.
• To explore the future role of AI in immunization science.

Main Methods:

• Review of current literature on AI in vaccinology.
• Analysis of AI's role in antigen discovery, epitope prediction, and immunogen design.
• Examination of AI's impact on clinical evaluation and scalability.

Main Results:

• AI offers computational power to process complex biological data for vaccine research.
• AI accelerates key stages of vaccine development, including antigen discovery and epitope prediction.
• AI integration signifies a shift towards faster, more precise, and scalable vaccine strategies.

Conclusions:

• AI represents a paradigm shift in vaccine development, enhancing efficiency and precision.
• Addressing translational challenges is crucial for realizing AI's full potential in vaccinology.
• AI is poised to significantly shape the future of immunization science.