Focus of research
[Forschungslinie 2]: Pharmacometric data analysis
Nonlinear mixed-effects modelling of selected antibiotics in special patient populations – with a focus on target-site pharmacokinetics
During the last decades, less new antibiotic drugs have been developed and bacterial resistance and antibiotic withdrawal have increased. Therefore, it is important to use existing antibiotics as scientifically rational as possible. Apart from the appropriate choice of antibiotics - potentially as drug combinations - based on their spectrum of activity, the achievement of effective drug concentration-time profiles at the target site (=site of infection) is an important factor in antibiotic therapy. The profiles required are dependent on the type of an antibiotic – e.g. for beta-lactam antibiotics, the antimicrobial activity is linked to the time above the minimal inhibitory concentration – but also on the susceptibility of the bacteria – e.g. for intermediate and resistant bacteria higher drug concentrations are needed than for susceptible bacteria. In special patient populations (e.g. critically ill patients, obese patients or neonates) the rational use of antibiotics is most important; however there is a lack of knowledge about the achieved drug concentration-time profiles. As the pharmacokinetics is altered in those patients, the profiles might differ, potentially requiring dose adjustments in those patients.
For most antibiotics, the target site is extravascular in the interstitial space fluid of a tissue or in other body fluids than blood, since the majority of bacterial infections occur there. Today, the method of choice to measure drug concentrations over time directly at the target site is microdialysis, a minimally invasive sampling technique used for the continuous measurement of unbound, active drug concentrations in e.g. the interstitial space fluid.
My PhD project deals with the analysis of pharmacokinetic (PK) data (plasma/serum and microdialysis drug concentration data) and pharmacodynamic (PD) data (e.g. disease scores, inflammation marker, mortality rate) from clinical trials in special patient populations using the nonlinear mixed-effects modelling approach. Based on the clinical PK data mathematical PK models will be developed which shall describe the drug concentration-time profiles in the populations as well as the variability between and within patients. Additionally, a covariate analysis will be performed to identify patients factors (e.g. demographics and pathophysiologic characteristics) explaining the PK variability in the populations. Those PK models shall then be linked to the outcome (PD data) in the patients. Ultimately, the models shall be used to verify or optimise current antibiotic dosing regimens in special patient populations with respect to effective drug concentration-time profiles in plasma/serum or at target site to finally improve therapeutic success and reduce risk of under/overdosing and bacterial resistance development.