Fraunhofer Institute for Manufacturing Engineering and Automation
In-Silico Human Modeling
For evidence-based therapy, the connection between the function and properties of the medical device, the physiology, biomechanics, and pathology of the patient, and the surgical procedure must be established. Only from the interactions between the endoprosthesis or implant and the patient can comprehensible, objective decisions be made about whether and how well the artificial joint will function. These complex relationships cannot be investigated using testing machines.
The “In-Silico Human Modeling” research team at Fraunhofer IPA develops musculoskeletal virtual human and patient models and conducts in-silico studies of implants for ankle, knee, hip, elbow, and shoulder joints. In our simulation models, we can map any dysfunctional joints caused, for example, by neuromuscular diseases or muscular imbalances. This enables us to analyze reconstructive surgical procedures on the musculoskeletal system of patients and the function of joint implants, and to illustrate the effects on the musculoskeletal system. This makes it possible to support surgeons and implant manufacturers in their decision-making in the operating room or in the development of new implants by providing a better understanding of the interaction between the implant and the (virtual) patient. In addition, in silico studies with virtual patient cohorts open up new potential for reducing the duration and costs of clinical trials.
Process of the In-Silico Physiological-Biomechanical Human Modeling (ISTH) platform
In-Silico Human Modeling Platform for Biomechanical Research on the Musculoskeletal System
We develop three-dimensional, physiological-anatomical simulation models of the musculoskeletal system, derived from MRI and CT data. These models incorporate detailed structures of skeletal muscles and connective tissues. Our muscle force-driven finite element simulation models are used for biomechanical research on the locomotor system, examining various joints, from the ankle to the shoulder.
The developed models can be applied both in musculoskeletal fundamental research and in industrial applications, such as for virtual surgical planning to support surgical decisions, for patient-centred product development and evaluation, as well as for virtual (in-silico) clinical trials in medical technology.
In-silico research of surgical interventions
The surgical treatment of musculoskeletal disorders is always associated with uncertainties, particularly when making critical decisions about the correction size. Every surgical intervention affects the muscular balance system of the joint in different ways. To address this problem, we develop virtual simulation methods to analyse the biomechanical effects of surgical interventions on the physiological, muscle force-driven joint movement (dynamics).
Examples of our research in collaboration with university hospitals include Achillies tendon lengthening (Z-plasty) for drop foot conditions, cruciate ligament reconstruction of the knee and amputation techniques. Our goal is to provide surgeons with deeper, physics-based insights into the consequences of their decisions. For this purpose, we also simulate specific muscular imbalances and neuromuscular disorders of the affected joints.
Our approach allows us to study both established and innovative surgical procedures to better understand their impact on joint physiology and consequently the musculoskeletal system. This will help to improve the outcomes of surgical interventions and therapies.
Functional patient-centred analyses of endoprosthetics, prosthetics, and orthotics
We investigate the mechanical stress, function, and stability of endoprosthetics, prosthetics, and orthotics under various loading scenarios through detailed structural analysis using the finite element method (FEM), which cannot be experimentally tested. Through the coupled biomechanical interactions between, for example, an endoprosthesis (size, design, material properties, and joint systems) and virtual patients, we can make more realistic statements about the functionality of the endoprosthesis and its positioning in the joint.
Our goal is to enable a comprehensible physiological-biomechanical function and load testing of endoprosthetics, prosthetics, and orthotics based on virtual patients. This is intended to make therapy more efficient on the one hand and to facilitate more patient-centred innovations on the other.
In-silico clinical trials for regulatory approval in the MedTech sector
Through the development of virtual patient cohorts of the musculoskeletal system, representing specifically defined patient subpopulations, we can realistically test implants biomechanically and functionally for their intended use in In-Silico Clinical Trials (ISCT).
This enables us to examine implants and surgical interventions in conjunction with real clinical studies through comprehensible in-silico studies and generate additional evidence. In the long term, this allows companies to reduce the costs and duration of approval processes.
Additionally, we continuously work on the further development of in-silico methods as well as on the processes for verification and validation of the simulation models to ensure their accuracy and reliability.