Translational systems biology of inflammation: Potential applications to personalized medicine

Qi Mi, Nicole Yee Key Li, Cordelia Ziraldo, Ali Ghuma, Maxim Mikheev, Robert Squires, David O. Okonkwo, Katherine Verdolini-Abbott, Gregory Constantine, Gary An, Yoram Vodovotz*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

55 Scopus citations

Abstract

A central goal of industrialized nations is to provide personalized, pre-emptive and predictive medicine, while maintaining healthcare costs at a minimum. To do so, we must confront and gain an understanding of inflammation, a complex, nonlinear process central to many diseases that affect both industrialized and developing nations. Herein, we describe the work aimed at creating a rational, engineering-oriented and evidence-based synthesis of inflammation geared towards rapid clinical application. This comprehensive approach, which we call 'Translational Systems Biology, to date has been utilized for in silico studies of sepsis, trauma/hemorrhage/traumatic brain injury, acute liver failure and wound healing. This framework has now allowed us to suggest how to modulate acute inflammation in a rational and individually optimized fashion using engineering principles applied to a biohybrid device. We suggest that we are on the cusp of fulfilling the promise of in silico modeling for personalized medicine for inflammatory disease.

Original languageEnglish
Pages (from-to)549-559
Number of pages11
JournalPersonalized Medicine
Volume7
Issue number5
DOIs
StatePublished - Sep 2010
Externally publishedYes

Keywords

  • inflammation
  • modeling
  • systems biology

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