A Systems Engineering Perspective on Homeostasis and Disease
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View metadata, citation and similar papers at core.ac.uk brought to you by CORE PERSPECTIVE ARTICLE published: 09 Septemberprovided by 2013 Frontiers - Publisher Connector BIOENGINEERING AND BIOTECHNOLOGY doi: 10.3389/fbioe.2013.00006 A systems engineering perspective on homeostasis and disease Yoram Vodovotz 1,2, Gary An3 and Ioannis P.Androulakis 4,5,6* 1 Department of Surgery, University of Pittsburgh, Pittsburgh, PA, USA 2 Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA 3 Department of Surgery, The University of Chicago, Chicago, IL, USA 4 Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, USA 5 Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, USA 6 Department of Surgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA Edited by: Engineered systems are coupled networks of interacting sub-systems, whose dynamics Xiaogang Wu, Indiana are constrained to requirements of robustness and flexibility.They have evolved by design University-Purdue University Indianapolis, USA to optimize function in a changing environment and maintain responses within ranges. Reviewed by: Analysis, synthesis, and design of complex supply chains aim to identify and explore the Osbaldo Resendis-Antonio, laws governing optimally integrated systems. Optimality expresses balance between con- Universidad Nacional Autónoma de flicting objectives while resiliency results from dynamic interactions among elements. Our México, Mexico increasing understanding of life’s multi-scale architecture suggests that living systems Zuxi Wang, Huazhong University of Science and Technology, China share similar characteristics with much to be learned about biological complexity from Lifan Zeng, Indiana University, USA engineered systems. If health reflects a dynamically stable integration of molecules, cell, *Correspondence: tissues, and organs; disease indicates displacement compensated for and corrected by Ioannis P.Androulakis, Department of activation and combination of feedback mechanisms through interconnected networks. In Biomedical Engineering, Rutgers this article, we draw analogies between concepts in systems engineering and conceptual University, 599 Taylor Road, Piscataway, NJ 08854, USA models of health and disease; establish connections between these concepts and phys- e-mail: [email protected] iologic modeling; and describe how these mirror onto the physiological counterparts of engineered systems. Keywords: systems biology, inflammation, trauma, systems engineering, humans INTRODUCTION as networks of dynamic components with identified boundaries Genome sequencing and high-throughput technologies have rev- and rules that guide their response (An et al., 2008; Foteinou et al., olutionized our approach to addressing biological questions. The 2009a,b; Vodovotz, 2010; McGuire et al., 2011). Given the high advent of these methods has created the opportunity to perturb inter-dependence among the constituent parts of a living sys- biological systems and observe genome-scale cellular responses tem and the non-intuitiveness of non-linear biological responses, (Ideker et al., 2001; Huang et al., 2005). Systems biology was the living organism may be viewed as a structure sharing the introduced as a means by which to describe scientific inquiries fundamental characteristics of “system of systems”: autonomy, through a global approach to elucidate, quantify, model, and synergism, connectivity, diversity and resilience (Sauser et al., potentially reverse engineer biological processes and mechanisms 2010). (Cassman et al., 2007; Rigoutsos and Stephanopoulos, 2007). Sys- With our increasing understanding of life’s multi-scale trans- tems biology has allowed us to address the question of how hierarchical architecture, it has been suggested that living systems cells behave as integrated systems rather than as mere sums share characteristics common to engineered systems and that of their parts (Wiley et al., 2003; Palsson, 2011). Mathematical there is much to be learned about biological complexity from formalisms have been developed that use mechanistic informa- engineered systems (Csete and Doyle, 2002; Doyle and Csete, tion and physiological knowledge to simulate behaviors at the 2011). This is not to say that biological systems are engineered organism level and provide a mechanistic basis for pathophysi- systems: biological systems are clearly distinct and different by ology (An et al., 2008). This development was, to a great extent, virtue of having resulting from evolution as opposed to design. driven by a desire to “::: encourage [physicians] to make the However, there are some similarities between their consequent subtle but important distinction between [clinical] outcomes organization and that of engineered systems that can provide use- and [biological] processes” (Buchman, 2009). If health repre- ful insights (D’Onofrio and An, 2010). For instance, engineered sents a living organism’s ability to maintain stability in the face systems can be perceived as coupled networks of interacting sub- of changing internal and external environments, then illness can systems, whose dynamics are constrained to tight requirements of be defined as the failure to accommodate these changes (Ahn robustness (to maintain safe operation) on one hand, and main- et al., 2006). Systems-based research considers living organisms taining a certain degree of flexibility to accommodate changeover www.frontiersin.org September 2013 | Volume 1 | Article 6 | 1 Vodovotz et al. A systems engineering perspective on homeostasis and disease on the other. The aim of analysis, synthesis, and design of com- gained the ability to assess globally the nature of the “factors” plex supply chains is to identify the laws governing optimally and “controls” at a cellular and molecular level. The terminol- integrated systems. Optimality of operations is not a uniquely ogy that is now used has evolved from the time of Bernard and defined property and usually expresses the decision maker’s bal- Cannon, and we now talk about the concept that the “mecha- ance between alternative, often conflicting, objectives. Both bio- nisms for maintaining this stability [of the milieu intérieur] require logical and engineered complex constructs have evolved through sensors to recognize discrepancies between the sensed and set multiple iterations, the former by natural processes and the lat- of acceptable values and require effectors that reduce those dis- ter by design, to optimize function in a dynamically changing crepancies – i.e., negative feedback systems (Goldstein and Kopin, environment by maintaining systemic responses within acceptable 2007).” ranges. Deviation from these limits leads to possibly irreversible We note that, nearly 100 years ago, physiologists were using damage. Stability and resiliency of these constructs results from terms that are quite common in systems engineering parlance dynamic interactions among constitutive elements. The precise such as: open system, disturbance, automatic adjustment, negative definition and prediction of complex outcomes dependent on feedback, steady state, signal detectors, a processor, and an effector these traits is critical in the diagnosis and treatment of many dis- organ controlled through “negative feedback servo-mechanisms” ease processes, such as inflammatory diseases (Vodovotz and An, (Buchman, 1996) to imply the existence of control architectures 2013). that dissipate disturbances so as to maintain“good health”(home- In this article, we attempt to draw analogies between fun- ostasis). By extension, therefore, if good health reflects a dynam- damental concepts pervasive in systems engineering theory and ically stable and harmonic integration of molecules, cell, tissues, practice and conceptual/theoretical models of health and disease, and organs, then disease indicates displacement which is compen- with particular examples in the setting of inflammatory diseases. sated for and corrected by the appropriate activation and combi- We opt to establish connections between these concepts and phys- nation of feedback mechanisms through interconnected networks iologic modeling, as well as how these concepts mirror themselves (Buchman, 2002). onto critical aspects of notional physiological counterparts of engineered systems. SYSTEMS ENGINEERING PRINCIPLES IN THE CONTEXT OF PHYSIOLOGICAL MODELING A SYSTEMS VIEW OF HOMEOSTASIS In the setting of engineered systems, modeling and simulation In the 1920s, Kahn presented his rendition of a human and his fun- complements theory and experimentation since, with advances in damental physiological functions in the form of interconnected computational power, mathematical models enhance the ability processing units forming an industriepalast (a chemical plant) of engineers to manage complexity, to explore new solutions effi- (Debschitz et al., 2009). These units exchange mass and energy, ciently and effectively, and, potentially, to increase the speed of among themselves and with the environment, so as to maintain innovation (Quarteroni, 2009). This approach has had, arguably, proper function by appropriate physico-chemical transformations significant impact in (operational or process) systems engineer- of mass while producing and consuming energy. Around the ing, a specific field of engineering that looks beyond individual same time period, Cannon was beginning to lay the foundations,