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.

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

Russo G.
Primo
Writing – Original Draft Preparation
;
Pappalardo F.
Ultimo
Supervision
2020-01-01

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.
2020
agent-based models
artificial intelligence
Covid-19
epitope prediction
immune system modeling
systems biology
Vaccine development
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/472380
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