We solve hard problems that matter.

Computational Modeling and Simulation

Medical Device Design and Optimization

Our experts can provide an optimum solution for medical device development using computational modeling and simulation (CM&S), also known as computer aided engineering (CAE).  We use general linear/nonlinear mechanics and fully coupled engineering physics to design and optimize device design, evaluate the performance of devices (e.g., virtual testing such as fatigue life evaluation and RF heating related to MRI), and optimize design considering manufacturability (design for manufacturing) before physical prototyping.  By leveraging CM&S early in the product life cycle, we can significantly shorten the time and cost of product development.  We are active in research and publication with the ultimate goal of reducing the burden of the medical device development and approval process while improving or maintaining patient safety. Our experience dates back to using CAE for mechanical evaluations of the first coronary stent approved by the FDA.

At MED Institute we have expertise using state-of-the-art finite element software such as Abaqus and COMSOL Multiphysics to simulate a variety of complex problems including:

  • Topology and shape optimization
  • Linear and nonlinear structural analysis
  • Computational fluid dynamics (CFD) and fluid structure interaction (FSI)
  • Dynamic analysis
  • Multiphysics simulation with electromagnetic coupled heat transfer for RF-induced heating of medical devices during MRI*
  • Durability (fatigue life) evaluation.* Determination of constant life curve (fatigue endurance limit)
  • Modeling of biocompatible materials such as nitinol, stainless steel, cobalt chrome, titanium, and polymers for analysis
  • Heat transfer
  • Design for Manufacturing
  • Ongoing research collaboration with the Center for Devices and Radiological Health (CDRH) at FDA on the topic of computational modeling and simulation

* Regulatory authorities have accepted testing only the worst-case device identified by the analysis among the same family of devices, which has led to tremendous savings of testing time and costs for the medical device industry.