Rapid Identification of Optimal Combination Regimens for Pseudomonas aeruginosa

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 DESCRIPTION (provided by applicant): Ventilator-Requiring Hospital Acquired Bacterial pneumonia is a disease process with substantial mortality and morbidity. Resistance emergence, particularly with P. aeruginosa is common with monotherapy and is on the order of 33-50% in patients treated with monotherapy. It has been recently demonstrated that granulocytes are saturable for bacterial cell kill. Rapid lowering of the bacterial burden to less than the half-saturation point results in a return of granulocyte-mediated bacterial kill. Combination therapy is prudent for both the ability to obtain maximal kill rate and to suppress amplification of resistant subpopulations. Identifying optimal combination regimens is difficult and time consuming. It is the overarching aim of this proposal to develop a new method to rapidly and robustly identify optimal combination therapy that will provide maximal cell kill along with resistance suppression. The rapid cell kill will help reduce the bacterial burden below the half saturation point and bring the granulocytes "back on line". it is our intent to: 1) Develop a new rapid method to identify optimal combination chemotherapy regimens employing flow cytometry 2) Test regimens resulting from this method in the HFIM; we will look at 3 isogenic strains to ascertain the impact of different resistance mechanisms on cell kill and resistance emergence; we will employ state-of-the art mathematical models to analyze these experiments; we will then validate these findings in the murine PA pneumonia models 3) Quantitate the interaction of granulocytes and combination therapy on cell kill and resistance suppression. The use of flow cytometry, linked with the Greco mathematical model will allow statistically robust determination of synergy/ additivity/ antagonism. Exploration of these combinations in our Hollow Fiber Infection Model and murine P. aeruginosa pneumonia models will provide the validation that the regimens identified by the flow assay as optimal or non-optimal behave in the fashion predicted. The impact of regimen on granulocyte recruitment will be ascertained. All these experiments will be linked by state-of-the-art mathematical models. Optimal regimens will improve outcomes, suppress resistance amplification and speed recovery because of granulyte function return. Defining optimal antimicrobial combination regimens will generate several salutary outcomes: 1] resistance emergence will be suppressed 2] rapid bacterial kill will unsaturate granulocytes, adding 1.0-1.5 extra Logs of bacterial kill per day 3] clinical outcomes and (hopefully) time to extubation will be shortened because of the improved rate of kill. Taken together overall clinical outcomes will be improved.