Document Type

Article

Source of Publication

Informatics in Medicine Unlocked

Publication Date

1-1-2024

Abstract

Reverse vaccinology is an emerging concept in the field of vaccine development as it facilitates the identification of potential vaccine candidates. Biomedical research has been revolutionized with the recent innovations in Generative Artificial Intelligence (AI) and Large Language Models (LLMs). The intersection of these two technologies is explored in this study. In this study, the impact of Generative AI and LLMs in the field of vaccinology is explored. Through a comprehensive analysis of existing research, prospective use cases, and an experimental case study, this research highlights that LLMs and Generative AI have the potential to enhance the efficiency and accuracy of vaccine candidate identification. This work also discusses the ethical and privacy challenges, such as data consent and potential biases, raised by such applications that require careful consideration. This study paves the way for experts, researchers, and policymakers to further investigate the role and impact of Generative AI and LLM in vaccinology and medicine.

ISSN

2352-9148

Publisher

Elsevier BV

Volume

48

Disciplines

Computer Sciences

Keywords

AI, AI ethics, Generative AI, Large language models (LLMs), Reverse vaccinology, Vaccine candidate identification, Vaccines

Scopus ID

85196551163

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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