Use numerical simulation & in-silico simulation to improve medical devices

numerical simulation and mathematical models allows for 2x faster time to market with simq

Up to 2X faster time to market for medical devices

numerical simulation and computational models, partial differential equations lead to cost reduction with simq

Up to 50% reduced R&D costs

Numerical Simulation for such models through computational methods with simq

Improved quality and safety for your medical components and systems

Numerical Simulation for basic concepts and complex interactions with simq

Optimized medical devices tailored to individual patient needs

A major leap forward in the development of medical technology

Simulation in the approval process

Applying simulation with the latest guidelines in a regulatory-compliant manner

Efficient testing of implants

Virtual Testing Laboratory

Cost and time saving testing of implant components and systems

Tailored simulation for each patient

Patient-Specific Simulation

Simulating how implants interact with a patient’s body

Monitoring of medical devices placed on the market

Post Market Surveillance

Continuous performance and safety verification for medical devices placed on the market using simulation

Discover our webinar and learn more about in silico medicine

Computational modeling in the Medical Device approval process

How to accelerate medical device R&D through in silico technologies

Dr. Sven Herrmann
Director Consulting & Seminars

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A numerical simulation is a calculation that is run on a computer following a program that implements a mathematical model for a physical system.

Numerical simulations are required to study the behavior of systems whose mathematical models are too complex to provide analytical solutions, as in most nonlinear systems.

At Simq, we use numerical simulation in our software solutions, for example, to digitally test the quality and safety of implants.

In research and development, numerical simulation is a very popular tool in all situations in which the practical experimental outlay is too high or no analytical solutions are known for the specific problem.

Numerical simulation represents difficult or non-measurable phenomena with reasonable outlay.

In addition, numerical simulation enables parameter studies to be carried out quickly and automatically under varying boundary conditions and facilitates the application of optimization algorithms.

Numerical simulation is a key to medical research and personalized medicine.

Numerical simulation can help to reduce R&D costs by up to 50% and speed up the time to market medical devices.

 With numerical simulation, you can also improve the quality and safety of medical components and systems by virtually testing more and including different variants that would not have been feasible with conventional methods.

In any case, the results are always optimized for medical devices tailored to individual patient needs with the help of numerical simulation.

Numerical simulation has numerous applications and can be integrated into medical software solutions for clinical trials and more.

At Simq, we integrate numerical simulation in our software solutions and have identified the following use cases for services:

  1. In the approval process, we apply simulation with the latest guidelines in a regulatory-compliant manner to support faster approval through in silico tests.

  2. Virtual testing laboratory to digitally test the function and strength of implants and shorten development cycles 

  3. Patient-specific simulation to better understand the implant behavior in a patient’s body and to efficiently evaluate and verify custom implants.

  4. Post-Market Surveillance to efficiently generate digital evidence for post-market clinical follow-ups on the function and safety of medical devices.

There are many numerical methods used for the simulation of engineering problems.

Among them, the finite difference method (FDM) and the finite element method (FEM) are the most commonly used.

The FDM provides a point-by-point approximation to a problem with grid points partitioning the geometry along each coordinate axis. 

The FEM model, on the other hand, provides a piecewise approximation to a problem with a collection of elements that subdivide the geometry along the boundaries.

The FDM solves the governing equations by direct differentiation along each coordinate axis.

Thus, it can run very fast.

The FEM solves the governing equations by discretizing the domain with elements of a selected shape and assembling them into the entire system.

Thus it usually runs slower than the FDM.

The FDM is mostly used for solving fluid mechanics and heat transfer problems, often with stationary boundaries, but it is impossible to use FDM for solving problems with large strain/deformation.

The FEM has more advantages in solving problems with large deformation and can be used for nearly all kinds of engineering problems with complex geometry and material combinations.

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