Our Research Mission
is to be recognised as an interdisciplinary research team
applying high scientific standards and innovative methodologies
advancing mechanistic understanding of drug-system relation
in a quantitative, integrated experimental / in silico approach
to ultimately foster rational use of medicines
while empowering young scientists to
perform clinically relevant research
The focus of our research lies in the optimisation of drug therapy for patient populations with high unmet medical and societal need, so called “vulnerable populations”, e.g. patients with cancer, intensive care patients, paediatric, pregnant or adipose patients. Our research aims to quantitatively and over time characterise the complex interactions between patient and drug by means of (patho-)physiology- and mechanism-based models and to use these to derive new concepts and recommendations of therapy.
Our research area, pharmacometrics & systems biology, is transdisciplinary and combines
- experimental concepts (Research pillar 1): Bioanalysis/microdialysis and in vitro systems/cell culture and
- theoretical concepts (Research pillar 2): Pharmacometric data analysis
Thereby, in vivo (clinical, partly preclinical), ex vivo and in vitro and in silico approaches are applied.
Based on our previous results, comprising mainly the development of empiric pharmacokinetic and pharmacodynamic models for drugs, we increasingly focus on mechanistic, i.e. physiology-motivated and mechanism-based models, integrating knowledge of cellular and molecular kinetics and dynamics to a larger extent. The spectrum of investigated medicines covers innovative monoclonal antibodies and paediatric formulations of glucocorticoides as well as licenced antiinfectives or cytostatics.
In bioanalysis, the focus is on the development of valid methods to determine traces of concentrations of drugs and their metabolites or biomarkers in complex biological matrices (blood, plasma, ultrafiltrate, skin, interstitial fluid, bone, etc.). To analyse these samples qualitatively and quantitatively we employ classical HPLC bioanalytics and high-resolution LC-MS/MS systems (s. PharmaMS; https://www.bcp.fu-berlin.de/pharmazie/institut/PharmaMS/index.html).
Particularly the understanding of the spectrum of metabolites and their contribution to therapeutical success or failure is gaining more and more importance. We have already generated various hypotheses for cytostatic and antiinfective drugs or drugs in development to enhance the mechanistic understanding of the effects of parent compounds and metabolites.
By using microdialysis, a minimally invasive technique, we accomplished the step from determination of drugs in blood to their site of action. The bioanalytical challenge is to reliably measure traces of concentrations of drugs, metabolites or biomarkers in small sample volumes (few nano- or microliters) over time. Not yet described in literature, we were able to establish this technique in long-term studies in humans. Additionally, we characterised the microdialysis technique extensively in vitro. By now, microdialysis is used in vivo in preclinical and clinical studies in healthy and even critically ill patients. Furthermore, we have started to evaluate various approaches to determine the pathophysiological status at the site of action: valid methods for markers (i.e. inflammatory status) are developed to differentiate between healthy and diseased state as well as disease progression and the therapeutic benefit.
In in vitro systems, we focus on the investigation of mechanisms and establishment of effect parameters to characterise drug effects: these in vitro systems allow an extensive and systematic investigation of mode of actions in cell culture and the identification of in vitro markers predictive of the therapeutic outcome. For instance, valid parameters determining the drug effect of antiinfective and anti-tumour drugs can be generated. Here, concentration-time profiles of drugs, either determined by using microdialysis at the site of action or predicted by pharmacometric models, can be mimicked in vitro. Based on the time-varying drug concentrations, antiinfective effects and potential emergence of resistance over time can be determined, forming the basis to develop semimechanistic pharmacometric models to predict the therapeutic outcome of a patient. Moreover, antimicrobial combination therapies and their beneficial use for the treatment of infections caused by drug resistant bacteria are investigated in trans-European consortia.
Experimental or clinical data obtained by Research pillar 1 or through collaborations in clinical studies form the basis for the development of new, predictive pharmacometric models. These integrate additionally relevant physiological, pathophysiological, anatomical and systems biology features of an organism. Microdialysis data measured in interstitial fluid and obtained from various clinical trials are particularly appropriate to consider systems-related processes in these models and gives us the opportunity to directly assess the target site pharmacokinetics of antiinfective drugs. Additionally, by analysis of patient-specific characteristics, so-called covariates, as factors influential on the organism or drug therapy, we aim to enhance the understanding of a disease and its progression as well as cure and its progression (under drug therapy) and to consequently individualise drug treatment.
The modelling and simulation activities applied in various projects partly realised by third-party funding are sophisticated and computationally-intensive and are thus realised by means of “high performance computing” on a Linux cluster (s. Soroban; www.zedat.fu-berlin.de/HPC/EN/Soroban).
In the fields of antiinfective and tumour therapy we have already generated new knowledge regarding interactions of drugs and the organ, e.g. on the interaction between monoclonal antibodies with anti-antibodies. Furthermore, we investigate the impact of genetic variability (e.g. CYP polymorphisms) on pharmacokinetic processes, identify patients with risk of therapy failure and derive individual dosing adaptations based the respective genotype and phenotype. Similarly, we also develop models characterising the dose-limiting toxicity of classical cytostatic drugs, e.g. long-term myelosuppression and peripheral neuropathy. These model-based approaches are useful to predict treatment progress and to give recommendations for more rational dosing regimens for individual patients or patient subgroups.
In many research projects we are collaborating with scientists in larger consortia at national and international level, e.g.
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