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WIREs Syst Biol Med
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Systems engineering meets quantitative systems pharmacology: from low‐level targets to engaging the host defenses

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Quantitative systems pharmacology aims at systematizing, in a model‐based manner, the integration of systems biology and pharmacology in an effort to rationalize the process of assessing the ability of a drug to enhance well‐being by off‐setting the effects of a disease. Systems engineering, on the other hand, has enabled us to develop principles and methodologies for designing and operating engineered networks of structures exploring the integration of the underlying governing (design) laws. Although the computational tools which have resulted in major advances in the design, analysis, and operation of complex engineered structures have had tremendous success in the analysis of systems pharmacology models, it is argued in this opinion paper, that exploring the underlying conceptual foundation of complex systems engineering will enable us to move toward integrated models at the host level to explore, and possibly, induce synergies between low‐level drug targets and higher level, systemic, defense mechanisms. This is an approach which would require refocusing of the key activities; however, it is likely the more promising approach as we enter the new era of personalized and precision medicine. We finally argue for the development of an allostatic approach to quantitative systems pharmacology and the development of an integrated framework for considering drugs in their broader context, beyond their local site of action. WIREs Syst Biol Med 2015, 7:101–112. doi: 10.1002/wsbm.1294 This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Physiology > Mammalian Physiology in Health and Disease Translational, Genomic, and Systems Medicine > Translational Medicine
(top) Notional equivalence between CoBS and CoES as ‘horizontally’‐integrated networked sub‐structures interchanging information and communicating messages. (bottom) Equivalent network structures (cell signaling/metabolic network on the left: Reprinted with permission from Ref . Copyright 2000 Elsevier; chemical process network structure of the right: Reprinted with permission from Ref . Copyright 2011 John Wiley and Sons), extended vertically, underlie the higher level organization. High(er) level substructure communication is the result of ‘messages’ produced by low(er) level information. Communication exchanges are therefore explicit within a given level, but also implicit across levels.
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(top) Simplified representation of the systems pharmacology ‘supply chain’. Often drugs are considered as ‘ligands’ (L) binding on appropriate ‘receptors’ (R). Drug bioavailability, i.e., concentration of L, is often determined by the drug's pharmacokinetics PK (obtained via appropriate physiologically based PK—PBPK—models). Binding of the drug on its receptor will induce a ‘signal’ (C) which will induce an appropriate cascade of ‘signals’ eventually inducing a cellular response, likely mediated by alteration of transcription/translation events. Cellular responses induce physiological effects by appropriate modulation of the release of various mediators. Responses are represented by appropriate pharmacodynamics/pharmacogenomics models (PD/PG) (bottom) The information flow is the aforementioned ‘chain’ of events is rarely linear and feed‐forward. Signals emanating from each event feedback to upstream nodes either within the same level of organization (e.g., within a same signaling pathway) or across levels of organization (e.g., the product of cellular metabolism in one tissue type may act as a signal to a different tissue type)
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Models of Systems Properties and Processes > Mechanistic Models
Physiology > Mammalian Physiology in Health and Disease
Translational, Genomic, and Systems Medicine > Translational Medicine

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