From data to immunity: the role of machine learning in advancing malaria vaccine research: a scoping review.

ABSTRACT:

Background

Malaria remains a significant global health burden, necessitating the development of effective vaccines. Traditional vaccine development is challenged by the complexity of the Plasmodium parasite and lengthy empirical processes. Machine learning (ML) offers a promising avenue to accelerate and enhance vaccine research.

Aim

This review synthesizes recent advances in the application of ML to malaria vaccine research, focusing on immunological signature identification, antigen discovery, and predictive modeling of vaccine efficacy, to highlight its transformative potential.

Methods

A targeted literature search was conducted for peer-reviewed articles, reviews, and systematic analyses published between 2017 and 2025. Studies directly addressing ML or AI in mala

SUBMITTER: Khanday S 

PROVIDER: S-EPMC12570413 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature