title: Complexity modeling: identify instability early.
abstract: Biological systems are innately complex, display nonlinear behavior, and respond to both disease and its treatment in similar complex ways. Complex systems display self-organization and predictive behavior along a range of possible states, often referred to as chaotic behavior, and can be both characterized and quantified in terms of this chaotic behavior, which defined strange attractors (ρ) and variability. In this context, disease can be characterized as a difference in a disease state ρ and a healthy ρ. Furthermore, effectiveness of treatment can be defined as a minimization problem to decrease the phase-state difference between disease and health ρ values, such that effective treatment is defined as the ability to restore the healthy ρ. Importantly, this approach will be effective without anything being known about the physiologic processes that define health or disease. The implication is that this approach is a powerful tool to define the determinants of instability as compared with normal variability, to answer why disease is not healthy, and to identify all potentially effective treatment options independent of known pharmacology and physiology.
authors.affiliation: Department of Critical Care Medicine, University of Pittsburgh, Pittsburg, PA, USA. pinskymr@upmc.edu
authors.forename: Michael R
authors.initials: MR
authors.lastname: Pinsky
mesh_terms: D054058:Acute Coronary Syndrome / Q000503:physiopathology; D004194:Disease; D017709:Fractals; D006262:Health; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D017711:Nonlinear Dynamics; D018805:Sepsis / Q000503:physiopathology; D013598:Systems Theory