AI-powered digital twins for orthopedics

Understand bone healing. Rethink treatment.

OSORA connects patient information, biomechanics and biology to explore how fixation and loading may shape healing over time — for fracture management, interactive education and implant R&D.

OSORA simulation of a femur with an implant

A fracture image is a snapshot. Healing is a process.

OSORA models predict how mechanics and tissue development interact over time. This makes it possible to compare scenarios, expose assumptions and discuss expected healing trajectories in context.

Simulated femur with intramedullary nail: bone density, callus and implant stress.

From case data to a simulated healing trajectory.

Patient information, fracture geometry, fixation and loading define the model. OSORA then follows how mechanics and tissue development interact over time, making it possible to compare scenarios rather than isolated snapshots.

A postoperative femur radiograph transitions into a cutaway computational model and three simulated healing stages.
One case moves from imaging to a computational model and two simulated healing trajectories.
  1. 01

    Define the case

    Bring together patient information, fracture geometry, fixation and loading conditions.

  2. 02

    Follow healing over time

    Model how mechanics, load sharing and tissue development may change across the healing trajectory.

  3. 03

    Compare and interpret scenarios

    Place alternatives side by side, make assumptions visible and discuss the results in context.

Built on research. Applied in collaboration.

OSORA combines scientific foundations with clinical, educational and engineering questions.

Built on published research

Peer-reviewed work and public studies document the simulation methods and the questions they can address.

Developed with clinical and engineering partners

We shape workflows, assumptions and study designs around real clinical and product-development questions.

Applied in teaching and case discussions

Virtual cases help course leaders and participants compare scenarios and make biomechanical reasoning visible.

Latest publication

Predicting nonunion – a hybrid machine-learning model combining patient factors and mechanobiological simulation features exceeds clinician accuracy

A retrospective study of tibial shaft fractures from four German trauma centres compared clinicians, an established risk score, the OSORA healing simulation and machine-learning models. Combining patient factors with simulation features identified more of the later nonunions than the clinicians did.

Armbruster J, Lamadé-Dootz F, Mattern N, Steinhausen ES, Hackl S, Reumann MK, Stengel D, Niemeyer F, Grützner PA, Freischmidt H. Bone & Joint Research. 2026;15(10):1196–1205. doi:10.1302/2046-3758.1510.BJR-2025-0788.R1

Read the article
patients with tibial shaft fractures from four trauma centres, 20 of whom developed a nonunion
98
sensitivity of the hybrid model for a later nonunion
80 %
negative predictive value of the hybrid model
94 %

Insights

OSORA is part of the Hospital of the Future at MEDICA 2026

We are participating within the Hospital of the Future area. Make sure to visit us and experience, how OSsistant will transform patient journeys in orthopedic & trauma care.

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Meet us at MEDICA 2026