Towards systems immunology of critical illness at scale: from single cell ‘omics to digital twins

Yoram Vodovotz*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations

Abstract

Single-cell ‘omics methodology has yielded unprecedented insights based largely on data-centric informatics for reducing, and thus interpreting, massive datasets. In parallel, parsimonious mathematical modeling based on abstractions of pathobiology has also yielded major insights into inflammation and immunity, with these models being extended to describe multi-organ disease pathophysiology as the basis of ‘digital twins’ and in silico clinical trials. The integration of these distinct methods at scale can drive both basic and translational advances, especially in the context of critical illness, including diseases such as COVID-19. Here, I explore achievements and argue the challenges that are inherent to the integration of data-driven and mechanistic modeling approaches, highlighting the potential of modeling-based strategies for rational immune system reprogramming.

Original languageEnglish
Pages (from-to)345-355
Number of pages11
JournalTrends in Immunology
Volume44
Issue number5
DOIs
StatePublished - May 2023
Externally publishedYes

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