Computational Biomechanics

In addition to in-vitro and in-vivo experiments, computational models have established themselves as a valuable tool for investigating biological processes and systems. So-called in-silico experiments can reproduce a variety of scenarios cost-effectively and in the shortest possible time. These insights help to plan and carry out in-vivo and in-vitro experiments. This accelerates scientific discoveries and allows clinical approaches to be designed more efficiently. Furthermore, mathematical models foster the understanding of highly complex biological relationships. For example, the simulation of stress distribution in bones and joints can be used to optimize the development of dental and orthopaedic products such as implants. Multiscale modeling integrates data at different scales and provides comprehensive insights into biomechanical processes. Machine learning algorithms predict disease progression and treatment outcomes, thus enabling personalized medicine. Furthermore, growth processes in biofilms can be modeled, providing a unique insight into the interaction of biological processes. The further development of these models and computer methods at IKM promises more precise, personalized and effective interventions in healthcare in the future.