Population based engineering to treat the maximum number of patients.

Proper anatomical and physiological performance of implants is crucial for a successful clinical outcome. Statistical analysis and virtual fitting based on imaging data of a high number of patients has crucial benefits compared to conventional approaches:

  • Optimize the design to treat the maximum number of patients
  • Reduce the risk of e.g. device – vessel misalignment, inaccurate sizing, unexpected variabilities in the patient’s anatomy
  • Compared with conventional cadaver studies, virtual fitting is a more accurate and economical way for determining the device fit and identifying areas for improvement
  • Cost-effective solution for including a large number of patients and anatomy variations in the design study even before manufacturing a prototype
  • Better prepare bench testing, animal studies and clinical trials
Virtual studies prior to animal trials

Virtual implantation for common large animal models prior to animal trials has several benefits:

  • Learn more about the different anatomical characteristics compared to humans and between animal models to choose the right one for the animal trial
  • Replacement of animal trials in the early product development phases, as device developers can quickly test the design virtually in a wide range of animal models
  • Limit the use of animals in the long-term and avoiding implantations in specific animals if the virtual implant shows e.g. that there is not enough space
  • Refining animal experiments because more specific data can be used to specify certain measurements needed for the implant to fit in order to minimise the risk of too small or too large animals ordered
  • Evaluate the anatomical constraints retrospectively in detail based on the imaging data in case an implantation has failed
Support the regulatory approval process
Source: Prediction of the sources of evidence for regulatory approval by the FDA related Medical Device Innovation Consortium

The requirements for safety and efficacy of medical devices are constantly increasing leading to higher costs and time to market for the manufacturer. Computer-aided simulations are proving to be particularly promising in accelerating the approval process and at the same time further increasing patient safety, in addition to classical approaches such as laboratory tests, animal models and clinical studies.

The FDA and ASME are strongly supporting this development with new guidelines (FDA Guidance 1807) and a V&V standard (V&V40 for Computational Modeling for Medical Devices). “FDA’s Office of Science and Engineering Laboratories (OSEL) has committed significant resources for transforming computational modeling from a valuable scientific tool to a valuable regulatory tool because of its potential for significant cost-savings in evaluating medical devices, simulating performance under scenarios that may not be possible with human use or that could more effectively be evaluated with simulation.” [FDA]

  • Justify design adjustments of the device
  • Determine and justify anatomical and morphological eligibility or exclusion criteria for proper patient selection and/or correct implant size
  • Enroll the right patients for a clinical trial and evaluate suitability of each patient in detail prior to implantation
  • Increase evaluation confidence by investigating aspects of device fitting/performance in many more clinically-relevant cases
  • Replace traditional, more burdensome data collection from traditional models

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