Integrating Data-Driven and Mechanistic Models of the Inflammatory Response in Sepsis and Trauma

Azhar, Nabil; Mi, Qi; Ziraldo, Cordelia; Buliga, Marius; Constantine, Gregory; Vodovotz, Yoram

doi:10.1007/978-1-4614-8008-2_8

Cited by 7 publications

(8 citation statements)

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“…Ultimately, however, computational models are by definition hypotheses ( 20 ). Both mechanistic models and some classes of machine learning models (e.g., a network depiction of the data), are forms of hypotheses about relationships, and so there should not be a tension between these in silico approaches and the “pure” hypothesis-driven approaches ( 23 , 24 ).…”

Section: Current and Future Research Models: Roles For Big Data Artimentioning

confidence: 99%

Prioritized Research for the Prevention, Treatment, and Reversal of Chronic Disease: Recommendations From the Lifestyle Medicine Research Summit

Vodovotz

Barnard

et al. 2020

Front. Med.

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Declining life expectancy and increasing all-cause mortality in the United States have been associated with unhealthy behaviors, socioecological factors, and preventable disease. A growing body of basic science, clinical research, and population health evidence points to the benefits of healthy behaviors, environments and policies to maintain health and prevent, treat, and reverse the root causes of common chronic diseases. Similarly, innovations in research methodologies, standards of evidence, emergence of unique study cohorts, and breakthroughs in data analytics and modeling create new possibilities for producing biomedical knowledge and clinical translation. To understand these advances and inform future directions research, The Lifestyle Medicine Research Summit was convened at the University of Pittsburgh on December 4–5, 2019. The Summit's goal was to review current status and define research priorities in the six core areas of lifestyle medicine: plant-predominant nutrition, physical activity, sleep, stress, addictive behaviors, and positive psychology/social connection. Forty invited subject matter experts (1) reviewed existing knowledge and gaps relating lifestyle behaviors to common chronic diseases, such as cardiovascular disease, diabetes, many cancers, inflammatory- and immune-related disorders and other conditions; and (2) discussed the potential for applying cutting-edge molecular, cellular, epigenetic and emerging science knowledge and computational methodologies, research designs, and study cohorts to accelerate clinical applications across all six domains of lifestyle medicine. Notably, federal health agencies, such as the Department of Defense and Veterans Administration have begun to adopt “whole-person health and performance” models that address these lifestyle and environmental root causes of chronic disease and associated morbidity, mortality, and cost. Recommendations strongly support leveraging emerging research methodologies, systems biology, and computational modeling in order to accelerate effective clinical and population solutions to improve health and reduce societal costs. New and alternative hierarchies of evidence are also be needed in order to assess the quality of evidence and develop evidence-based guidelines on lifestyle medicine. Children and underserved populations were identified as prioritized groups to study. The COVID-19 pandemic, which disproportionately impacts people with chronic diseases that are amenable to effective lifestyle medicine interventions, makes the Summit's findings and recommendations for future research particularly timely and relevant.

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Section: Current and Future Research Models: Roles For Big Data Artimentioning

confidence: 99%

Prioritized Research for the Prevention, Treatment, and Reversal of Chronic Disease: Recommendations From the Lifestyle Medicine Research Summit

Vodovotz

Barnard

et al. 2020

Front. Med.

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“…Plasma inflammatory mediators were assessed over 0-24 h postinjury in hypotensive blunt trauma patients (A) or 0-5 h postinjury in C57Bl/6 mice (B) by LuminexÔ. Dynamic Bayesian network inference was carried out as described previously (3,18,19,50,158). Red: chemokines.…”

Section: Translational Systems Biology Of Inflammationmentioning

confidence: 99%

“…We and others have leveraged data-driven modeling methods to (i) avoid possible bias in selection of variables; (ii) discern principal drivers, key nodes, and positive/negative feedback; and (iii) facilitate the rapid analysis of complex, dynamic, multidimensional datasets with the ultimate goal of generating predictive mechanistic models (11,18,145). We carried out an iterative process of evidence-based modeling (146,148), consisting of biomarker assay, data analysis/data-driven modeling to discern main drivers of a given inflammatory response (67), literature mining to link these principal drivers based on well-vetted and likely mechanisms, calibration to the original data, and then validation using data separate from the calibration data.…”

Section: Data-driven Mathematical Modelsmentioning

confidence: 99%

Insights into the Role of Chemokines, Damage-Associated Molecular Patterns, and Lymphocyte-Derived Mediators from Computational Models of Trauma-Induced Inflammation

Namas

et al. 2015

Antioxidants & Redox Signaling

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Significance: Traumatic injury elicits a complex, dynamic, multidimensional inflammatory response that is intertwined with complications such as multiple organ dysfunction and nosocomial infection. The complex interplay between inflammation and physiology in critical illness remains a challenge for translational research, including the extrapolation to human disease from animal models. Recent Advances: Over the past decade, we and others have attempted to decipher the biocomplexity of inflammation in these settings of acute illness, using computational models to improve clinical translation. In silico modeling has been suggested as a computationally based framework for integrating data derived from basic biology experiments as well as preclinical and clinical studies. Critical Issues: Extensive studies in cells, mice, and human blunt trauma patients have led us to suggest (i) that while an adequate level of inflammation is required for healing post-trauma, inflammation can be harmful when it becomes self-sustaining via a damage-associated molecular pattern/Toll-like receptor-driven feed-forward circuit; (ii) that chemokines play a central regulatory role in driving either self-resolving or selfmaintaining inflammation that drives the early activation of both classical innate and more recently recognized lymphoid pathways; and (iii) the presence of multiple thresholds and feedback loops, which could significantly affect the propagation of inflammation across multiple body compartments. Future Directions: These insights from data-driven models into the primary drivers and interconnected networks of inflammation have been used to generate mechanistic computational models. Together, these models may be used to gain basic insights as well as serving to help define novel biomarkers and therapeutic targets. Antioxid. Redox Signal. 23, 1370-1387.Trauma: A Significant Burden T rauma/hemorrhagic shock remains the leading cause of death in patients younger than 45 years (70). It is the third leading cause of death worldwide, resulting in five million or 10% of all deaths annually and thus considered the fifth leading cause of significant disability (137). Traumatic injury is a pandemic disease, one that affects every nation in the world regardless of the level of socioeconomic development (70, 71).The disease is acute in onset, but often results in chronic, debilitating health problems that have effects beyond the individual victims. The financial impact of traumatic injuries is staggering: in 2000 in the United States, 10% of hospital discharges were due to injuries, and the direct cost of treating 50 million injury cases was $80.2 billion, with an estimated

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“…The estimation of the fundamental quantity F in Equation (1) via the control and output variables u and y will be detailed in Section 2.2. It connects our approach to the data-driven viewpoint which has been adopted in control engineering (see, e.g., [39,42,67,68]) and in studies about inflammation (see, e.g., [9,20,69,84]).…”

Section: Remarkmentioning

confidence: 99%

“…As in previous control studies using this model, we assume that the state components P and D in Equations (9) and (12) are not measurable; whereas, the states N and C a in Equations (10) and (12), respectively, are:…”

Section: Control Designmentioning

confidence: 99%

Toward a model-free feedback control synthesis for treating acute inflammation

Bara

Fliesś

Join

et al. 2018

Journal of Theoretical Biology

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An effective and patient-specific feedback control synthesis for inflammation resolution is still an ongoing research area. A strategy consisting of manipulating a pro and anti-inflammatory mediator is considered here as used in some promising model-based control studies. These earlier studies, unfortunately, suffer from the difficultly of calibration due to the heterogeneity of individual patient responses even under similar initial conditions. We exploit a new model-free control approach and its corresponding "intelligent" controllers for this biomedical problem. A crucial feature of the proposed control problem is as follows: the two most important outputs which must be driven to their respective desired states are sensorless. This difficulty is overcome by assigning suitable reference trajectories to the other two outputs that do have sensors. A mathematical model, via a system of ordinary differential equations, is nevertheless employed as a "virtual" patient for in silico testing. We display several simulation results with respect to the most varied situations, which highlight the effectiveness of our viewpoint.

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Integrating Data-Driven and Mechanistic Models of the Inflammatory Response in Sepsis and Trauma

Cited by 7 publications

References 84 publications

Prioritized Research for the Prevention, Treatment, and Reversal of Chronic Disease: Recommendations From the Lifestyle Medicine Research Summit

Prioritized Research for the Prevention, Treatment, and Reversal of Chronic Disease: Recommendations From the Lifestyle Medicine Research Summit

Insights into the Role of Chemokines, Damage-Associated Molecular Patterns, and Lymphocyte-Derived Mediators from Computational Models of Trauma-Induced Inflammation

Toward a model-free feedback control synthesis for treating acute inflammation

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