Pneumonia is considered to be one of the leading causes of death worldwide.
The outcome depends on both, proper antibiotic treatment and the effectivity
of the immune response of the host. However, due to the complexity of the
immunologic cascade initiated during infection, the latter cannot be predicted
easily. We construct a biomathematical model of the murine immune response
during infection with pneumococcus aiming at predicting the outcome of
antibiotic treatment. The model consists of a number of non-linear ordinary
differential equations describing dynamics of pneumococcal population, the
inflammatory cytokine IL-6, neutrophils and macrophages fighting the infection
and destruction of alveolar tissue due to pneumococcus. Equations were derived
by translating known biological mechanisms and assuming certain response
kinetics. Antibiotic therapy is modelled by a transient depletion of bacteria.
Unknown model parameters were determined by fitting the predictions of the
model to data sets derived from mice experiments of pneumococcal lung
infection with and without antibiotic treatment. Time series of pneumococcal
population, debris, neutrophils, activated epithelial cells, macrophages,
monocytes and IL-6 serum concentrations were available for this purpose. The
antibiotics Ampicillin and Moxifloxacin were considered. Parameter fittings
resulted in a good agreement of model and data for all experimental scenarios.
Identifiability of parameters is also estimated. The model can be used to
predict the performance of alternative schedules of antibiotic treatment. We
conclude that we established a biomathematical model of pneumococcal lung
infection in mice allowing predictions regarding the outcome of different
schedules of antibiotic treatment. We aim at translating the model to the
human situation in the near future.
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit
A Biomathematical Model of Pneumococcal Lung Infection and Antibiotic
Treatment in Mice
PLoS ONE. - 11 (2016), 5, Artikel Nr. e0156047
Charité - Universitätsmedizin Berlin