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The combination of artificial intelligence and systems biology for intelligent vaccine design

Research output: Contribution to journalLiterature reviewpeer-review

Abstract

Introduction: A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes and reducing the costs and time involved in drug research and development. Areas covered: This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline. The topics include a detailed description of epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases. Expert opinion: Artificial intelligence and systems biology offer the opportunity to avoid the inefficiencies and failures that arise in the classical vaccine development pipeline. One promising solution is the combination of both methodologies in a multiscale perspective through an accurate pipeline. We are entering an ‘in silico era’ in which scientific partnerships, including a more and more increasing creation of an ‘ecosystem’ of collaboration and multidisciplinary approach, are relevant for addressing the long and risky road of vaccine discovery and development. In this context, regulatory guidance should be developed to qualify the in silico trials as evidence for intelligent vaccine development.
Original languageEnglish
Pages (from-to)1267-1281
Number of pages15
JournalExpert Opinion on Drug Discovery
Volume15
Issue number11
DOIs
Publication statusPublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • agent-based models
  • artificial intelligence
  • Covid-19
  • epitope prediction
  • immune system modeling
  • systems biology
  • Vaccine development

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