Mathematical and Statistical Modeling of Acute Inflammation

Clermont, Gilles; Chow, Carson C.; Constantine, Gregory; Vodovotz, Yoram; Bartels, John

doi:10.1007/978-3-642-17103-1_43

Cited by 11 publications

(7 citation statements)

References 24 publications

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“…We initially developed a model of acute inflammatory response to a generic gram-negative bacterium (13). This model consists of a system of ordinary differential equations that model the time course of local concentration or cell density of the key components of this response such as pathogen, pathogen-derived toxins, proinflammatory and anti-inflammatory mediators, the coagulation cascade, and global tissue damage/dysfunction (29). The equations are constructed from influence diagrams depicting known biological interactions among model components as documented in the existing scientific literature.…”

Section: Simulating Anthrax Infectionmentioning

confidence: 99%

Comparison of Clinical Manifestations and Outcome of Community-Acquired Bloodstream Infections Among the Oldest Old, Elderly, and Adult Patients

et al. 2007

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Bacillus anthracis (anthrax) can trigger an acute inflammatory response that results in multisystem organ failure and death. Previously, we developed a mathematical model of acute inflammation after gram-negative infection that had been matched qualitatively to literature data. We modified the properties of the invading bacteria in that model to those specific to B. anthracis and simulated the host response to anthrax infection. We simulated treatment strategies against anthrax in a genetically diverse population including the following: (1) antibiotic treatment initiated at various time points, (2) antiprotective antigen vaccine, and (3) a combination of antibiotics and vaccine. In agreement with studies in mice, our simulations showed that antibiotics only improve survival if administered early in the course of anthrax infection. Vaccination that leads to the formation of antibodies to protective antigen is anti-inflammatory and beneficial in averting shock and improving survival. However, antibodies to protective antigen alone are predicted not to be universally protective against anthrax infection. Rather, our simulations suggest that an optimal strategy would require both vaccination and antibiotic administration.

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Section: Simulating Anthrax Infectionmentioning

confidence: 99%

Comparison of Clinical Manifestations and Outcome of Community-Acquired Bloodstream Infections Among the Oldest Old, Elderly, and Adult Patients

et al. 2007

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“…Model-based approaches attempt to quantify the causal relationships between the components manifesting and driving the onset, maintenance, and resolution of the inflammatory response. These representations can vary from statistical and correlational (Clermont et al, 2004) to mechanistic (Foteinou, Calvano, et al, 2009c); from deterministic and continuous (J. D. Scheff et al, 2011) to discrete and stochastic (An et al, 2009; Dong et al, 2010; Nguyen et al, 2013).…”

Section: Towards Integrative Models In Systems Biology and Systemsmentioning

confidence: 99%

On the analysis of complex biological supply chains: From process systems engineering to quantitative systems pharmacology

Rao

Scherholz

Hartmanshenn

et al. 2017

Computers & Chemical Engineering

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The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

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“…Data-driven methods [50,59,70], including network-based approaches [59,63,71–85] have indeed proven to be quite useful in systems biology applications. Principal components are orthonormal linear combinations of the data vector, with the property that they carry the largest variances in several orthogonal directions.…”

Section: Integrating Data-driven and Mechanistic Modeling Of Intracelmentioning

confidence: 99%

Translational Systems Approaches to the Biology of Inflammation and Healing

Vodovotz

Constantine

Faeder

et al. 2010

Immunopharmacology and Immunotoxicology

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Inflammation is a complex, non-linear process central to many of the diseases that affect both developed and emerging nations. A systems-based understanding of inflammation, coupled to translational applications, is therefore necessary for efficient development of drugs and devices, for streamlining analyses at the level of populations, and for the implementation of personalized medicine. We have carried out an iterative and ongoing program of literature analysis, generation of prospective data, data analysis, and computational modeling in various experimental and clinical inflammatory disease settings. These simulations have been used to gain basic insights into the inflammatory response under baseline, gene-knockout, and drug-treated experimental animals for in silico studies associated with the clinical settings of sepsis, trauma, acute liver failure, and wound healing to create patient-specific simulations in polytrauma, traumatic brain injury, and vocal fold inflammation; and to gain insight into host-pathogen interactions in malaria, necrotizing enterocolitis, and sepsis. These simulations have converged with other systems biology approaches (e.g., functional genomics) to aid in the design of new drugs or devices geared towards modulating inflammation. Since they include both circulating and tissue-level inflammatory mediators, these simulations transcend typical cytokine networks by associating inflammatory processes with tissue/organ impacts via tissue damage/dysfunction. This framework has now allowed us to suggest how to modulate acute inflammation in a rational, individually optimized fashion. This plethora of computational and intertwined experimental/engineering approaches is the cornerstone of Translational Systems Biology approaches for inflammatory diseases.

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Mathematical and Statistical Modeling of Acute Inflammation

Cited by 11 publications

References 24 publications

Comparison of Clinical Manifestations and Outcome of Community-Acquired Bloodstream Infections Among the Oldest Old, Elderly, and Adult Patients

Comparison of Clinical Manifestations and Outcome of Community-Acquired Bloodstream Infections Among the Oldest Old, Elderly, and Adult Patients

On the analysis of complex biological supply chains: From process systems engineering to quantitative systems pharmacology

Translational Systems Approaches to the Biology of Inflammation and Healing

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