SP 1

Optimize therapy, novel strategies

SP1: Evaluating Pharmacokinetic/ Pharmacodynamic and innate immune parameters in the pyelonephritis environment

Pyelonephritis is frequent and causes substantial morbidity. Uropathogens causing pyelonephritis become increasingly antibiotic-resistant, hindering successful treatment. Patients suffering from pyelonephritis are clinically very heterogeneous and the parameters which decide treatment success or failure are not comprehensively understood. This project aims to elucidate the changes in blood and urine in human pyelonephritis and the effect of innate immune parameters on anti-infective treatment. This project transfers knowledge from deeply phenotyped pyelonephritis patients into pharmacological models, pursuing specific clinical and experimental aims. The alteration of blood and urine of pyelonephritis and control groups will be characterized by analyzing the physico-chemical properties, the proteome with a focus on antimicrobial peptides, and the number and differentiation status of myeloid cells. Alterations will be analyzed bioinformatically and correlated with the severity and clinical course of pyelonephritis. Non- clinical, ex vivo pharmacological models for investigation of antibiotics, namely pharmacokinetic and pharmacodynamic assessments, will be adapted to the peculiar pyelonephritis environment, including antimicrobial peptides. Selected myeloid cells will be incorporated into the pharmacological study by using the hollow-fiber model to investigate the additional anti-infective effect of immune cells in pharmacokinetic and pharmacodynamic models. The goal of this proposal is to better understand the molecular and cellular changes in blood and urine during pyelonephritis and its effect on anti-infective treatment. This will optimize available treatment strategies and delineate novel strategies for pyelonephritis therapy.

The results from clinical phenotyping and in-depth analysis of liquid biopsies will enable us clinically better stratify patients at risk for a more severe outcome of pyelonephritis. Eventually, parameters improving the defense against bacterial renal infection can be translated into clinical practice. In addition, the pharmacological models will help optimizing anti-infective treatment, improve clinical cure and decrease the emergence of antimicrobial resistance of causative pathogens. Adaptation of the pharmacological models to the renal environment will build a platform to better assess potential antibiotic candidates for suitability for treatment of pyelonephritis. In the end a more personalized approach will result to treat this highly heterogenous infectious entity of pyelonephritis.