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The key to the development of a successful implant is an understanding of the effect of bone remodelling on its long-term fixation. In this study, clinically observed patterns of bone remodelling have been compared with computer-based predictions for one particular design of prosthesis, the Thrust Plate Prosthesis (Centerpulse Orthopedics, Winterthur, Switzerland). Three-dimensional finite-element models were created using geometrical and bone density data obtained from CT scanning. Results from the bone remodelling simulation indicated that varying the relative rate of bone deposition/resorption and the interfacial conditions between the bone and the implant could produce the trend towards the two clinically observed patterns of remodelling.

The resorption of bone in the human femur following total hip arthroplasty is recognized to be related to the loading in the bone surrounding the prosthesis. However, the precise nature of the mechanical signal that influences the biological remodelling activity of the bone is not completely understood. In this study, a validated finite element modelling methodology was combined with a numerical algorithm to simulate the biological changes over time. This was used to produce bone remodelling predictions for an implanted thrust plate prosthesis (Centerpulse Orthopedics Limited) in a patient specific bone model. The analysis was then repeated using different mechanical signals to drive the remodelling algorithm. The results of these simulations were then compared to the patient-specific clinical data, to distinguish which of the candidate signals produced predictions consistent with the clinical evidence. Good agreement was found for a range of strain energy based signals and also deviatoric remodelling signals. The results, however, did not support the use of compressive dilatational strain as a candidate remodelling signal.

The orthopedic device industry relies heavily on clinical evaluation to confirm the safety, performance, and clinical benefits of its implants. Limited sample size often prevents these studies from capturing the full spectrum of patient variability and real-life implant use. The device industry is accustomed to simulating benchtop tests with numerical methods and recent developments now enable virtual “in silico clinical trials” (ISCT). In this article, we describe how the advancement of computer modeling has naturally led to ISCT; outline the potential benefits of ISCT to patients, healthcare systems, manufacturers, and regulators; and identify how hurdles associated with ISCT may be overcome. In particular, we highlight a process for defining the relevant patient risks to address with ISCT, the utility of a versatile software pipeline, the necessity to ensure model credibility, and the goal of limiting regulatory uncertainty. By complementing—not replacing—traditional clinical trials with computational evidence, ISCT provides a viable technical and regulatory strategy for characterizing the full spectrum of patients, clinical conditions, and configurations that are embodied in contemporary orthopedic implant systems.

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