Inside the human body, all biological systems, e.g. the nervous system, the cardiovascular system or the musculoskeletal system are interconnected and coupled with each other, i.e. nothing runs alone.

We want to understand the human body better. We ask ourselves, for example, how complex movement sequences are generated and controlled or how organs function. We are also interested in how diseases develop and how they can be successfully combated. For example, we contribute to the development of cancer therapies.

From large to small and vice versa

These are all difficult questions. To find answers, we need to understand the complex interaction of units of the human body at different size levels.

This starts with human cells as the smallest units. An average cell is 25 micrometers in diameter and is invisible to the human eye. An adult human is composed of approximately 75 trillion (1012) cells. The processes in individual cells influence our movements and the functioning of our organs. But changes at the organ and muscle level (e.g. mechanical forces) in turn influence individual cells. This is a complex interplay across many size scales.

To get closer to answers to our questions, we conduct research at different size scales: from the whole human, to organs, to cells, to the protein level.

Together for the people

Researchers from very different disciplines are working on this:

• Movement scientists and physicists measure human movement in everyday life and in sports.
• Biologists conduct experiments on cells and organs in the laboratory.
• Mathematicians and computer scientists develop computer models to explain these experiments and thus to better understand the function and mode of action of biological systems on different scales and to make predictions about behavior in different life situations (illness, age, athletic training).

Understanding the complex interplay of the many components in the human body is only possible through collaborative research across all disciplines. Our findings not only bring us closer to the mysteries of the body, but also contribute to improving human health and well-being.

Computer models of the human body or individual organ systems can support and advance both individual health care and the development of customized biomedical products. To do so, however, these models must reproduce the diverse interactions of biological systems at different structural levels. This requires extensive experimental data at the cell, organ, and organism levels. Furthermore, individual model predictions require the consideration of the variability of biological systems as well as the development of individualized multiscale models.

Models for complex biological systems

Our overall goal in SimTech is to develop detailed computational models of complex biological systems that couple different scales and heterogeneous data. Here, we focus our research on areas where coupled structure-function approaches play a central role and where there is an urgent need for development. These include neuromechanics, in particular the neuromuscular system, and proliferative and degenerative diseases. Our focus is on both the fundamental understanding of physiological and pathological relationships and their modeling as well as the establishment of new simulation methods.

The interaction of nerves and muscles

Our research on the neuromuscular system addresses general questions about the basic mechanisms of movement generation and movement control. In application-oriented studies, we use this knowledge to better understand neurodegenerative diseases, age-related changes and individual movement strategies and thereby optimize therapies. To this end, we are developing an integrative biophysical system model that encompasses muscle recruitment, physiology and mechanics. The necessary experimental data and model parameters are collected in our neuromechanics laboratory.

From simulation to therapy

Strategies for model-based optimization of proliferative disease treatment require a better understanding of mechanisms at the cellular level. Therefore, we couple data from novel single cell analysis techniques with averaged population data. This enables the development of multiscale modeling approaches for cell proliferation and tumor growth based on cancer subtype-specific mutations. The integration of individualized patient*in data into such a modeling-simulation-analysis cycle and the development of corresponding (multiscale) modeling approaches represents a link that is currently missing for model-based personalized cancer treatment.

We see our research as the cornerstone for future developments in human movement modeling and prediction, biotechnology, and individualized medical therapy.