Muscle Physiological and Disease Models

The research groups of Oliver Röhrle and Tobias Siebert investigate the musculoskeletal system to understand how different types of muscle — skeletal, smooth, and cardiac — generate force, adapt, and contribute to movement and organ function. Their work spans multiple scales, from cellular processes and tissue microstructure to whole-organ and multi-muscle systems. By combining biomechanics, physiology, and computational modeling, they aim to reveal the fundamental principles of muscle function in health and disease.

Muscles and organs are highly complex systems, where electrical activity, biochemical processes, and mechanical properties interact across many scales. Current experimental models cannot fully reproduce this interplay: organ function as a whole is difficult to capture, and it remains challenging to predict how interventions such as drugs, therapies, or surgeries affect tissue behavior and long-term adaptation.

To address these challenges, Röhrle’s group develops advanced multi-scale and multi-physics simulations of skeletal muscles and soft tissues, incorporating experimental data into in silico models. These models allow researchers to ask “what-if” questions and predict tissue responses to interventions such as drug delivery or rehabilitation therapies.

In parallel, Siebert’s team focuses on ex vivo muscle models to investigate the biomechanical properties of smooth, skeletal, and cardiac muscle. Their work provides the foundation for developing realistic in silico organ models of the bladder, stomach, intestine, and skeletal muscles. Such models not only improve our understanding of dysfunctions but also enable the simulation of medical procedures and their post-surgical effects on organ function.

By integrating computational modeling with experimental approaches, both groups advance alternatives to animal testing. In silico models and ex vivo setups create a bridge to lab-on-chip technologies, offering reproducible and ethically responsible ways to study muscle physiology and disease. These methods reduce the need for animal experiments while still capturing the complexity of living tissues.