The combination of artificial intelligence and systems biology for intelligent vaccine design.
Covid-19
Vaccine development
agent-based models
artificial intelligence
epitope prediction
immune system modeling
systems biology
Journal
Expert opinion on drug discovery
ISSN: 1746-045X
Titre abrégé: Expert Opin Drug Discov
Pays: England
ID NLM: 101295755
Informations de publication
Date de publication:
11 2020
11 2020
Historique:
pubmed:
15
7
2020
medline:
6
11
2020
entrez:
15
7
2020
Statut:
ppublish
Résumé
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. 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. 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.
Identifiants
pubmed: 32662677
doi: 10.1080/17460441.2020.1791076
doi:
Substances chimiques
COVID-19 Vaccines
0
Viral Vaccines
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM