Integrating data-driven and mechanistic models of the inflammatory response in sepsis and trauma

Nabil Azhar, Qi Mi, Cordelia Ziraldo, Marius Buliga, Gregory M. Constantine, Yoram Vodovotz*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

9 Scopus citations


Inflammation can drive both homeostasis and disease via dynamic, multiscale processes. The inflammatory response can be studied using multiplexed platforms, but there is no straightforward means by which to deal with the consequent data deluge in order to glean basic insights and clinically useful applications. Systems approaches, including data-driven and mechanistic computational modeling, have been employed in order to study the acute inflammatory response in the settings of trauma/hemorrhage and sepsis. Through combined data-driven and mechanistic modeling based on such meso-dimensional datasets, computational models of acute inflammation applicable to multiple preclinical species as well as humans were generated. A key hypothesis derived from these studies is that inflammation may be regulated via positive feedback loops that control switching between beneficial and detrimental inflammatory responses. Self-resolving inflammation may occur when specific signals feedback in a positive fashion to drive anti-inflammatory responses, while proinflammatory signals remain below certain thresholds. In contrast, self-amplifying, detrimental inflammation may occur when different signals feedback in a positive fashion to drive proinflammatory responses, setting in motion the positive feedback loop of inflammation → tissue damage/dysfunction → inflammation driven by damage-associated molecular pattern molecules. These insights may drive a future generation of targeted, personalized therapies for acute inflammation.

Original languageEnglish
Title of host publicationComplex Systems and Computational Biology Approaches to Acute Inflammation
PublisherSpringer New York
Number of pages15
ISBN (Electronic)9781461480082
ISBN (Print)1461480078, 9781461480075
StatePublished - 1 May 2013
Externally publishedYes


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