Pharmacist and Diploma-Pharmacist Johanna Seeger

Institute of Pharmacy
Clinical Pharmacy & Biochemistry
Freie Universität Berlin
Room 242
12169 Berlin
Curriculum Vitae
Since 05/2017 |
Doctoral student at the Dept. of Clinical Pharmacy & Biochemistry supervised by Prof. Dr. Charlotte Kloft at the Freie Universitaet Berlin |
07/2017 |
Registration as a Pharmacist |
11/2016 - 04/2017 |
Internship at Lichtenberg Apotheke, Berlin |
05/2016 - 10/2016 |
Diploma student in the Clinical Pharmacy, Prof. Dr. C. Kloft |
04/2012 - 03/2016 |
Studies of Pharmacy, Freie Universität Berlin |
09/2012 and 03/2013 |
Internship at Galenus-Apotheke, Berlin |
07/2009 |
Bachelor of Nursing, Protestant University of Applied Sciences Berlin |
06/2004 |
A-levels (Abitur), Katholische Theresienschule, Berlin |
Focus of research
Research pillar 1: Bioanalysis/microdialysis and in vitro systems/cell culture
In vitro investigations of pharmacokinetic-pharmacodynamic relations for optimisation of antibiotic therapy
Prevention of emergence and spread of antibiotic resistance is an important challenge in anti-infective therapy. Antibiotic resistance is promoted by poor therapy adherence, which can be related to adverse drug reactions, as well as by inefficient therapy regimens that result in insufficient drug concentrations at the infection site. This leads to selection of pathogens with low susceptibility against the antibiotic agent and spread of resistant strains. Therefore, dosing optimisation is of high importance for reducing adverse drug effects and emergence of resistance. Knowledge about the relationship between pharmacokinetics (PK) and pharmacodynamics (PD) of an antibiotic agent is crucial to characterise the pharmacodynamic effect of different dosing regimens of a drug. In silico simulations predict concentration-time profiles (C-t profiles) of certain dosing regimens and make it possible to mimic their PD effect in the dynamic in vitro infection model. Knowledge about bacterial growth and time kill behaviour is generated by quantification of antibiotic-exposed bacteria. Since the dynamic in vitro infection model provides drug exposures comparable to infection sites in humans, identification of appropriate dosing regimens for the treatment of particular infectious diseases is possible. At the same time, the investigation of bacterial characteristics, such as cell size and genetic properties, provides information about emergence of resistance and underlying resistance mechanisms. Thereby, dosing regimens that promote or prevent selection of resistant strains and emergence of resistance can be identified. The clinical relevance of different PK/PD parameters, which are used to describe PK/PD relations in antibiotic therapy, is a current topic of discussion. Data generated from dynamic in vitro experiments can contribute to the identification of the most predictive parameters.
The focus of my PhD project is the investigation of different dosing regimens of the fluoroquinolone levofloxacin (LEV) and its PD effects against the gram negative enterobacterium Escherichia coli (E. coli). Dosing optimisation for fluoroquinolones is of high importance, because next to beta-lactam antibiotics and aminoglycosides they belong to the “critical important” antimicrobials and spread of fluoroquinolone resistance is considered to be especially worrying. Furthermore, the serious adverse drug reactions of fluoroquinolones are a frequent subject of public criticism, which highlights the importance of dosing optimisation to promote therapy adherence and hereby reduce emergence and spread of resistance. E coli is a prevalent cause of bloodstream infections, urinary tract infections, skin and soft tissue infections and exposes increasing fluoroquinolone resistance. Besides alteration of target enzymes, such as bacterial DNA gyrase and topoisomerase IV, reduced intracellular antibiotic concentration due to decreased membrane permeability and expression of efflux pumps are most common resistance mechanisms.
The objective of my investigations in the dynamic in vitro infection model is the identification of resistance mechanisms resulting from different dosing regimens of LEV against E. coli, generating knowledge about PK/PD relations and hereby to contribute to the optimisation of antimicrobial therapy.