This article originally appeared on the KETIV Blog. To read the original article in its entirety, click HERE.
Before a life-saving medical device can be brought to market, the manufacturers need to navigate multiple government tests and trials from the FDA. Unfortunately, these tests and trials can take a long time and are sometimes compromised by external factors. This means that potentially revolutionary medical tools and devices can’t be used to save lives or improve the quality of life for patients.
Medical simulations have a long history dating back to the 18th century when models of human patients were created to show the effects of diseases, and animals were used for surgical training. Today, medical techniques have improved with computer modeling in biomedical engineering. This method allows medical professionals of all areas to simulate everything from patient flow in emergency rooms to the behavior of chronic diseases in a specific population. This technology can also now be used to support a regulatory submission.
However, the medical device industry’s biggest challenge is demonstrating that simulation testing is sufficient digital evidence for FDA approval of these devices. According to the FDA, submissions, “…often lack a clear rationale for why [computer simulation] models can be considered credible for the context of use.”
In a recent article on the KETIV blog, Graham Stevens of KETIV discussed the steps medical device manufacturers can take to boost simulation credibility and bring more innovative products to market faster. In addition, Stevens shares the benefits of using simulation techniques to gain FDA approval for medical devices:
The use of simulation in FDA approvals
The use of computer modeling and simulation (also known as “in silico” methods) in regulatory submissions is well established and rapidly increasing in line with Moore’s Law. Below are two of the most common ways this technology is used when seeking FDA clearance for medical devices.
In Silico Device Testing: This is when computational models simulate medical devices to demonstrate safety and/or effectiveness. Device testing models can be paired with patient models to simulate device performance under representative in vivo conditions.
In Silico Clinical Trial: This is when device performance is evaluated using a ‘virtual cohort’ of simulated virtual patients with realistic anatomical and physiological variability representing the indicated patient population.
The Benefits of Simulation (In Silico Trials) of Medical Devices
In silico testing is a powerful tool for evaluating the safety and performance of medical devices before they’re manufactured and introduced into the market. Whether the intention is to complement or replace physical trials, the in silico trial approach offers manufacturers several benefits over traditional testing methods. Below are some examples.
- In silico testing enables manufacturers to analyze a medical device’s performance in a controlled environment without the interference of external factors present in physical bench tests. This results in more accurate and reliable performance assessments.
- In silico testing accelerates the market launch of new medical devices by leveraging the high speed of computer simulation, allowing manufacturers to run thousands of tests in just seconds.
- In silico testing is considerably less expensive than physical alternatives.
- In silico testing enables manufacturers to simulate and examine edge cases, providing a comprehensive understanding of how a medical device performs in extreme conditions.
- In silico testing can uncover unexpected adverse events that may go undetected in limited study samples but frequently occur within the target population.
- In silico testing allows manufacturers to detect design limitations early, streamlining the development process, reducing costs, and expediting the availability of life-saving medical devices for patients.
- In silico testing reduces the cost and time associated with the pre-market evaluation of medical devices, enabling manufacturers to experiment with more high-risk products. This, in turn, drives innovation and advances in the field.
- In the event of a post-market failure, in silico testing allows manufacturers to quickly identify the root cause and restore the performance profile of a medical device.
- In silico testing reduces the likelihood of encountering functional issues with expensive hospital equipment, reducing capital expenditure and ensuring reliable operation.
The FDA Explains How to Demonstrate a Simulation Model is Credible for FDA Approval
Manufacturers of medical devices need to demonstrate their simulation models’ credibility to gain FDA approval. Fortunately, the FDA provides a nine-step process to follow (the Generalized Framework for Assessing Credibility of Computational Modeling in a Regulatory Submission.)
You can read about the nine steps in Assessing the Credibility of Computational Modeling and Simulation in Medical Device Submissions, published in December 2021. Or just read a brief summary below:
Step 1. Describe the specific question, decision, or concern to be addressed in the regulatory submission.
Step 2. Define the context of use (COU) of the computational model. The COU is a statement that defines the specific role and scope of the model.
Step 3. Determine the model risk (the possibility the model and simulation could be wrong.)
Step 4. Identify any credible evidence that supports the credibility of the computer model for the COU.
Step 5. Break down the analysis of verification, validation, or other sources of this credibility evidence.
Step 6. Perform a prospective adequacy assessment–if goals are achieved, will the credibility evidence be sufficient to support using the model for the COU?
Step 7. Execute the study.
Step 8. Perform a post-study adequacy assessment–does the credibility evidence support using the model for the COU?
Step 9. Prepare a report.
Simulation offers a powerful digital solution for manufacturers of medical devices, delivering increased accuracy, enhanced product design, improved safety, and reduced cost and time compared to traditional testing methods.
By leveraging simulation, manufacturers can achieve FDA approval for their products and bring safe, effective medical devices to market faster. But for simulation models to be considered credible digital evidence by the FDA, manufacturers have to jump through the hoops outlined in the Generalized Framework for Assessing Credibility of Computational Modeling in a Regulatory Submission.