| Abstract: |
| The global antimicrobial resistance crisis is a slow-motion tsunami. The lack of novel treatment options and the mounting resistance to currently approved agents are making a bad situation worse. Infections caused by Gram-negative bacteria are especially challenging to treat. Hence, refocusing efforts on combining in silico mathematical modeling strategies using both preclinical (in vitro and in vivo) and clinical pharmacokinetic/pharmacodynamic time course data to design and optimize antimicrobial treatment taking the interactions between host and pathogen into consideration is an attractive strategy. Using a systems based approach to model progression of bacterial infection taking the host immune response into consideration model enables us to understand the contribution of the host relative to drug treatment. Similarly, understanding immunodynamics in addition to viral kinetics within the host following influenza, an acute respiratory tract infection will enable us to determine the optimal time as well as dose and frequency of dosing antiviral treatment. |
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