Review on Systems Vaccinology and Predictive Vaccine Design

A 15.9 KB DOCX file authored by Nicole Simone De Lima Coelho and last updated on April 30, 2026. This document is a review article discussing the transition from empirical vaccinology to a predictive, systems-based approach. It examines the integration of multi-omics data, artificial intelligence, and addresses challenges related to reproducibility, algorithmic bias, and global equity.

Use Cases

• Literature review on systems immunology based on the document's critical examination of the field.
• Analysis of multi-omics integration strategies for vaccine design based on the described technological foundations.
• Study of ethical and regulatory challenges in data-driven vaccines based on the discussed considerations of governance and equity.
• Evaluation of AI applications and limitations in vaccinology based on the mentioned topics of predictive modeling and algorithmic bias.

Strengths

• File size is precisely 15.9 KB, indicating a concise document.
• License is clearly defined as CC-BY-4.0, allowing for open sharing and adaptation.
• Last update date is specified as 2026-04-30, suggesting recent maintenance.

Limitations

• The file is a review document (DOCX), not a structured dataset; row count and column definitions are absent.
• Description metadata is limited; actual data quality requires manual inspection after download.
• The 15.9 KB size indicates a very limited scope, likely containing only textual review content.

Provenance

Source

figshare, author Nicole Simone De Lima Coelho

Collection Method

Likely authored as a scholarly review.

Freshness

Last updated 2026-04-30 04:21:13; freshness should be verified.