LAPSE:2018.0190
Published Article
LAPSE:2018.0190
Modeling and Hemofiltration Treatment of Acute Inflammation
July 30, 2018
Abstract
The body responds to endotoxins by triggering the acute inflammatory response system to eliminate the threat posed by gram-negative bacteria (endotoxin) and restore health. However, an uncontrolled inflammatory response can lead to tissue damage, organ failure, and ultimately death; this is clinically known as sepsis. Mathematical models of acute inflammatory disease have the potential to guide treatment decisions in critically ill patients. In this work, an 8-state (8-D) differential equation model of the acute inflammatory response system to endotoxin challenge was developed. Endotoxin challenges at 3 and 12 mg/kg were administered to rats, and dynamic cytokine data for interleukin (IL)-6, tumor necrosis factor (TNF), and IL-10 were obtained and used to calibrate the model. Evaluation of competing model structures was performed by analyzing model predictions at 3, 6, and 12 mg/kg endotoxin challenges with respect to experimental data from rats. Subsequently, a model predictive control (MPC) algorithm was synthesized to control a hemoadsorption (HA) device, a blood purification treatment for acute inflammation. A particle filter (PF) algorithm was implemented to estimate the full state vector of the endotoxemic rat based on time series cytokine measurements. Treatment simulations show that: (i) the apparent primary mechanism of HA efficacy is white blood cell (WBC) capture, with cytokine capture a secondary benefit; and (ii) differential filtering of cytokines and WBC does not provide substantial improvement in treatment outcomes vs. existing HA devices.
The body responds to endotoxins by triggering the acute inflammatory response system to eliminate the threat posed by gram-negative bacteria (endotoxin) and restore health. However, an uncontrolled inflammatory response can lead to tissue damage, organ failure, and ultimately death; this is clinically known as sepsis. Mathematical models of acute inflammatory disease have the potential to guide treatment decisions in critically ill patients. In this work, an 8-state (8-D) differential equation model of the acute inflammatory response system to endotoxin challenge was developed. Endotoxin challenges at 3 and 12 mg/kg were administered to rats, and dynamic cytokine data for interleukin (IL)-6, tumor necrosis factor (TNF), and IL-10 were obtained and used to calibrate the model. Evaluation of competing model structures was performed by analyzing model predictions at 3, 6, and 12 mg/kg endotoxin challenges with respect to experimental data from rats. Subsequently, a model predictive control (MPC) algorithm was synthesized to control a hemoadsorption (HA) device, a blood purification treatment for acute inflammation. A particle filter (PF) algorithm was implemented to estimate the full state vector of the endotoxemic rat based on time series cytokine measurements. Treatment simulations show that: (i) the apparent primary mechanism of HA efficacy is white blood cell (WBC) capture, with cytokine capture a secondary benefit; and (ii) differential filtering of cytokines and WBC does not provide substantial improvement in treatment outcomes vs. existing HA devices.
Record ID
Keywords
cytokines, endotoxemia, hemoadsorption, inflammation, mathematical model, nonlinear MPC, particle filter, sepsis, state estimation
Subject
Suggested Citation
Parker RS, Hogg JS, Roy A, Kellum JA, Rimmelé T, Daun-Gruhn S, Fedorchak MV, Valenti IE, Federspiel WJ, Rubin J, Vodovotz Y, Lagoa C, Clermont G. Modeling and Hemofiltration Treatment of Acute Inflammation. (2018). LAPSE:2018.0190
Author Affiliations
Parker RS: Department of Chemical and Petroleum Engineering; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
Hogg JS: Carnegie Mellon⁻University of Pittsburgh Ph.D. Program in Computational Biology, 3501 Fifth Ave, 3064 BST3, Pittsburgh, PA 15260, USA
Roy A: Department of Chemical and Petroleum Engineering; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
Kellum JA: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
Rimmelé T: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
Daun-Gruhn S: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA; Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 15213, USA
Fedorchak MV: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA [ORCID]
Valenti IE: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
Federspiel WJ: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA
Rubin J: Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA 15261, USA
Vodovotz Y: McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA; Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 1
Lagoa C: Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 15213, USA
Clermont G: Department of Chemical and Petroleum Engineering; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
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Hogg JS: Carnegie Mellon⁻University of Pittsburgh Ph.D. Program in Computational Biology, 3501 Fifth Ave, 3064 BST3, Pittsburgh, PA 15260, USA
Roy A: Department of Chemical and Petroleum Engineering; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
Kellum JA: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
Rimmelé T: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
Daun-Gruhn S: Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA; Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 15213, USA
Fedorchak MV: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA [ORCID]
Valenti IE: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
Federspiel WJ: Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA
Rubin J: Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA 15261, USA
Vodovotz Y: McGowan Institute for Regenerative Medicine, University of Pittsburgh Medical Center, 450 Technology Dr, Suite 300, Pittsburgh, PA 15219, USA; Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 1
Lagoa C: Department of Surgery, University of Pittsburgh Medical Center, W944 Biomedical Sciences Tower, Pittsburgh, PA 15213, USA
Clermont G: Department of Chemical and Petroleum Engineering; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Critical Care Medicine, University of Pittsburgh Medical Center, 3550 Terrace St, Pittsburgh, PA 15213, USA
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Journal Name
Processes
Volume
4
Issue
4
Article Number
E38
Year
2016
Publication Date
2016-10-18
ISSN
2227-9717
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PII: pr4040038, Publication Type: Journal Article
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LAPSE:2018.0190
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https://doi.org/10.3390/pr4040038
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