Senior Researcher and Group Leader
Julius Wolff Institut, Berlin Institute of Health at Charité – Universitätsmedizin Berlin

Dr. Schmidt-Bleek trained in biology, molecular biology, and veterinary medicine at the University of Hamburg, the Freie Universität of Berlin, and Rheinland Pfalzische Technische Universität in Kaiserslautern. She completed post-doctoral training at the Julius Wolff Institut, Charité

Who have been your mentors?
My group leaders Hanna Schell and Jasmin Lienau were my direct mentors introducing me to research in Bone Biology, Hans-Dieter Volk was a mentor after I took over the research group from Hanna and Jasmin and of course close cooperation with Georg N. Duda was decisive for my career.

How are you currently applying computational models of cellular behavior to your bone fracture research program?
Computational modeling has gained in importance over time. In close cooperation with Sara Checas group here at the Julius Wolff Institut biomechanical strains and stresses were evaluated in our in vivo bone healing models. These analyses include the cellular behavior of different cell types important for bone formation with mechanical conditions considering their changes during the progressing bone healing phases. Thus, her models enabled a deeper understanding of the processes especially due to the continuous verification with either our pre-clinical models or patient data sets.

What are advantages and challenges associated with using computational models to inform biological or clinical research?
Advantages are the ability to simulate conditions and test hypotheses without the use of animal models. Vice versa newer developments even help us understand the results from our in vivo analyses in more detail. The aim to develop a computational histology for bone is very interesting as bone is known to be a very complicated tissue for histological analyses. The challenges are the multitude of influencing factors from which only a certain number can be included in the computational model – here the need to choose the “right” conditions to include in the modelling process are the most challenging.

Are there specific barriers that once addressed might make using computational models to inform ex vivo study design more common?
I do think that the validation of the developed models against in vivo samples is the best way to improve the models and their predictability especially if variable conditions can be applied for the model and the in vivo proof in parallel.

Can you speak to ways your multi-disciplinary collaboration informs your individual research programs?
Being involved in pre-clinical bone healing research we aim to keep our animal numbers as low as possible and also to extract as much information out of the samples gained from our in vivo models as possible. A thorough in vitro, ex vivo and in silico preparation of the actual in vivo work and a multidisciplinary analysis of the samples gives us the possibility to work with small group numbers in order to gain relevant results. This is only possible through a multi-disciplinary team.

How do your computational models account for the complexity of cell-matrix interactions and vascularization processes that are critical for bone healing in ex vivo systems?
The best way to address the complexity is to first understand the process targeted for computational modelling as well as possible in order to understand the most important factors that need to be included and varied within the model and then to verify the model against actual in vivo data.