Dynamic Computational Model of Symptomatic Bacteremia to Inform Bacterial Separation Treatment Requirements

Abstract

The rise of multi-drug resistance has decreased the effectiveness of antibiotics, which has led to increased mortality rates associated with symptomatic bacteremia, or bacterial sepsis. To combat decreasing antibiotic effectiveness, extracorporeal bacterial separation approaches have been proposed to capture and separate bacteria from blood. However, bacteremia is dynamic and involves host-pathogen interactions across various anatomical sites. We developed a mathematical model that quantitatively describes the kinetics of pathogenesis and progression of symptomatic bacteremia under various conditions, including bacterial separation therapy, to better understand disease mechanisms and quantitatively assess the biological impact of bacterial separation therapy. Model validity was tested against experimental data from published studies. This is the first multi-compartment model of symptomatic bacteremia in mammals that includes extracorporeal bacterial separation and antibiotic treatment, separately and in combination. The addition of an extracorporeal bacterial separation circuit reduced the predicted time of total bacteria clearance from the blood of an immunocompromised rodent by 49%, compared to antibiotic treatment alone. Implementation of bacterial separation therapy resulted in predicted multi-drug resistant bacterial clearance from the blood of a human in 97% less time than antibiotic treatment alone. The model also proposes a quantitative correlation between time-dependent bacterial load among tissues and bacteremia severity, analogous to the well-known ‘area under the curve’ for characterization of drug efficacy. The engineering-based mathematical model developed may be useful for informing the design of extracorporeal bacterial separation devices. This work enables the quantitative identification of the characteristics required of an extracorporeal bacteria separation device to provide biological benefit. These devices will potentially decrease the bacterial load in blood. Additionally, the devices may achieve bacterial separation rates that allow consequent acceleration of bacterial clearance in other tissues, inhibiting the progression of symptomatic bacteremia, including multi-drug resistant variations.

Optimization of Micromagnetic Separation for Bacteremia Treatment

“…The blood of the systemic circulation flows to and from each of the organs, except notably where blood is transported from the spleen to the liver via the portal vein. Additionally, the most significant modification from the model published by Miller et al [14] is the removal of the return pathway from the device to the blood. Here, it is assumed that any bacteria captured have no path of reentry into the circulatory system; consequently, uncaptured bacteria remain in the blood compartment.…”

“…To determine the efficacy of treatment, the area under the curve (AUC) in each of the compartments, computed via trapezoidal integration, was compared across flow rates and microsphere radii. As a quantifiable criterion, the time to go below a threshold of 1 CFU/mL in the bloodstream was also examined [14]. Table 2.…”

“…Table 2. Parameters for PBPK model of A. baumannii infection by compartment as given by Miller et al [14]. N = normal, IC = immunocompromised, AB = antibiotic + IC.…”

“…Several PBPK models of bacterial infection have been developed, one of the first being Cheewatrakoolpong et al's twocompartmental murine model [18]. Miller et al were the first to incorporate an extracorporeal pathogen removal device into an infection model [14]. A magnetic separation model was developed by Kang et al for their device, interrogating the role of the radius of their magnetic beads in separation efficiency from whole blood [19].…”

Optimization of Micromagnetic Separation for Bacteremia Treatment

“…PBPK models of bacterial infection have been in existence since Cheewatrakoolpong et al's two-compartmental murine model [7]. Miller et al were the first to incorporate an extracorporeal pathogen removal device into an infection model [8]. A magnetic separation model was developed by Kang et al for their device, interrogating the role of the radius of their magnetic beads in separation efficiency from whole blood [9].…”