Systems medicine: can mathematical models of disease help clinicians?

19 March 2010

Gilles Clermont
Director, Center for Inflammation and Regenerative Modeling
University of Pittsburgh


Physicians caring for individuals in the intensive care setting make time-critical diagnostic and therapeutic decisions based on incomplete information and moving physiology. Yet, 15% of patients still die in ICU, often as a direct consequence of inflammatory conditions such as severe infections. There is a growing consensus that the immune response to the assault of critical illness is often maladaptive and contributes in a major way to a poor prognosis in many patients. We will illustrate current efforts at bringing mathematical modeling at the bedside, from augmenting the clinicians' mental model of disease [1], to designing pharmacologic and device-based therapeutics. We will start with a simple model of the inflammatory response, extract high level insights, and draw parallels with recent randomized clinical trials. More complex models open the door to simulated clinical trials and suggest potential approaches to personalized therapies [2]. We will also discuss current efforts at overcoming obstacles to bringing modeling and computer intensive methods at the bedside [3, 4].


  1. S Zenker, J Rubin, G Clermont, "From inverse problems in mathematical physiology to quantitative differential diagnoses", PLoS Comp Biol 3:e204 2007. PubMed
  2. G Clermont, J Bartels, R Kumar, G Constantine, Y Vodovotz, C Chow, "In-silico design of clinical trials: a method coming of age", Crit Care Med 32:2061-70 2004. PubMed
  3. R S Parker, G Clermont, "Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenge", J R Soc Interface 2010. PubMed
  4. G Clermont et al, "Bridging the gap between systems biology and medicine", Genome Med 1:88 2009. PubMed

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