Mechanism‐Based Disease Progression Model Describing Host‐Pathogen Interactions During the Pathogenesis of Acinetobacter baumannii Pneumonia

Abstract

The emergence of highly resistant bacteria is a serious threat to global public health. The host immune response is vital for clearing bacteria from the infected host; however, the current drug development paradigm does not take host‐pathogen interactions into consideration. Here, we used a systems‐based approach to develop a quantitative, mechanism‐based disease progression model to describe bacterial dynamics, host immune response, and lung injury in an immunocompetent rat pneumonia model. Previously, Long‐Evans rats were infected with Acinetobacter baumannii (A. baumannii) strain 307‐0294 at five different inocula and total lung bacteria, interleukin‐1beta (IL‐1β), tumor necrosis factor‐α (TNF‐α), cytokine‐induced neutrophil chemoattractant 1 (CINC‐1), neutrophil counts, and albumin were quantified. Model development was conducted in ADAPT5 version 5.0.54 using a pooled approach with maximum likelihood estimation; all data were co‐modeled. The final model characterized host‐pathogen interactions during the natural time course of bacterial pneumonia. Parameters were estimated with good precision. Our expandable model will integrate drug effects to aid in the design of optimized antibiotic regimens.

A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6

“…A recently published analysis [35] utilizing a modelling approach more similar to the one presented here, relied on a hypothetical unobserved compartment of anti-inflammatory cytokines to model inhibition of TNF-α and IL-1β release. This approach would work similarly to our dynamic change in EC 50 for the acute tolerance, as both approaches ties cytokine inhibition directly to the pathogen burden.…”

A biomathematical model of immune response and barrier function in mice with pneumococcal lung infection

“…influenza: [ 37 ], fungal: [ 38 , 39 ]). A model of pneumonia caused by Acinetobacter baumannii is presented by Diep et al [ 40 ]. This model is based on rat data and describes bacterial population, neutrophils, albumin, and neutrophil-regulated cytokines and chemokines.…”

Combating Multidrug‐Resistant Bacteria by Integrating a Novel Target Site Penetration and Receptor Binding Assay Platform Into Translational Modeling

“…26 The next series of models characterized the inoculum effect (i.e., greatly diminished and/or slower bacterial killing at high compared with low initial inocula) for three antibiotic classes, [33][34][35][36] implemented pharmacogenomics data, 37,38 or characterized the effects of the immune system. [39][40][41][42][43] Optimizing treatment outcomes Subsequently, both empirical and mechanism-based models have been developed to rationally optimize antibiotic monotherapy and combination therapy dosage regimens based on in vitro and animal infection model data. [44][45][46][47][48][49] Monte Carlo simulations are often utilized to predict antibiotic efficacy in the presence of between patient variability in PKs.…”

“…As a substantial step forward, models were developed to simultaneously fit data on the growth and killing of the susceptible and resistant populations and were prospectively validated 26 . The next series of models characterized the inoculum effect (i.e., greatly diminished and/or slower bacterial killing at high compared with low initial inocula) for three antibiotic classes, 33–36 implemented pharmacogenomics data, 37,38 or characterized the effects of the immune system 39–43 …”