Mathematical modeling of community-acquired pneumonia patients
© BioMed Central Ltd 2009
Published: 11 November 2009
Sepsis is defined by the systemic response to an infection, governed by dynamic interactions between the tissues, immune cells and inflammatory mediators. We used the Immunetrics platform to build a large-scale mathematical model that encompasses these biological components. The model incorporates a virtual clinician, an automated system to examine simulated patients' status at clinically relevant intervals and administer standard of care interventions as necessary, thereby altering the dynamics of the disease state. The model reproduces many characteristics of systemic response to an infection, including the time course of cytokines, coagulation factors, clinical markers, early and late organ failure, and early versus late deaths.
The ordinary differential equation-based model was used to simulate the progression of sepsis over a 30-day hospital stay. This model was fit to published human endotoxemia data as well as data from severely septic community-acquired pneumonia (CAP) patients from the GenIMS study. The model was fit to 15 biomarkers and clinical markers, including mean arterial pressure, , IL-6, and PAI-1. PaO2, creatinine, TNFα
The ability of our model to reproduce a large variety of patients with a relatively small number of parameter changes illustrates the robustness of the underlying biological processes being modeled. The model may help identify real signals in immensely variable and noisy multidimensional sepsis patient data, and distinguish real patient responses from clinical study-site-related variability. This model is currently undergoing further validation. Future capabilities include assessment of risk and benefit of new drugs for sepsis or new treatment strategies (for example, early goal-directed therapy) in different patient cohorts.