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Simulation Benefits For The Healthcare Industry - FDA Approval

Simulation Assisted FDA Approval | CFD Consulting
August 1, 2017 By: Chris Mesibov

The challenges facing the healthcare industry are very unique. In Part 1, I explored many ways in which simulation can meet these challenges.  The development of new medical products require that companies clear a variety of very specific and costly hurdles, the most important of which is regulatory approval.  This post will discuss the ways that simulation can be used as part of the approval process.

Evidence for Regulatory Decisions

For decades, the Food & Drug Administration in the US, and CE in Europe, have been accepting simulation results as part of the approval process. The focus of this post will be on the FDA. The FDA recognizes the necessity of simulation results. To that end the FDA has created guidelines that provide product developers the process, procedures and modeling requirements for FDA approval submission. In addition, the Medical Device Innovation Consortium (MDIC), is a public-private group that has emerged in order to bring medical devices to patients more safely, quickly and cost effectively. The MDIC identifies and standardizes modeling and simulation validation requirements so that computer simulations can become an integral source of evidence of medical device safety, effectiveness and performance.

Simulation Assisted FDA Approval

Using simulation in conjunction with the FDA submission process provides unique opportunities for product developers. The typical FDA approval process is long and expensive. Also, the approval process could result in the FDA requesting measurement results or additional measurement results, and this could add difficulty and additional costs, and any approval question usually leads to more experiments.

Alternatively, providing simulation results can verify and validate the new solutions and assemble virtual FDA testing that occurs on a large number of patients.  As a result, the use of simulation can:

  • Shorten the approval process and FDA approval time 
  • Save significant costs thru assembling virtual large numbers of patients
  • Reduce the amount of physical testing

In the development process, MDIC compliant models can be generated at each stage:

  • Design Idea and feasibility – Virtual Prototyping
  • Design optimization
  • Parallel virtual modeling during the clinical phase
  • Providing simulation result data during FDA submission and at the regulatory decision
  • Any redesigns due to post market monitoring could feed discovered issues back into the simulation models
     

In Silico Testing Validation

In Silico is an industry accepted term meaning in silicon, or in the computer.

Validation of new products on a cohort of patients can occur virtually. For example: an array of patient bone data of various sizes and ages can be used to test an orthopedic implant. Using existing bone scan data taken from a multitude of patients, simulations can be performed to determine the performance of the implant on bones of various sizes and conditions. The testing can be performed using scripting to automate the simulation effort.  Ultimately the results then can be used for submission to the FDA.


Other important simulations to conduct include simulation to determine the effects of external influences such as radio frequency (RF) or microwave energy on implant/body interaction. An example of this is the amount of RF heating that occurs when the implant is exposed to strong electromagnetic fields, as during an MRI investigation. The strong magnetic field in a MRI chamber could cause tissue heating, the extent of which can be simulated accurately before any new product implant is placed in an actual patient.

The benefits that simulation can provide as part of the regulatory approval process are clear. There are other important benefits, including the ability to simulate very complex physics, such as the electromagnetic fields mentioned above. In Part 3 of this series, I will dig deeper into these complexities, and discuss simulation of electronic medical devices.