The new article highlights the aspects related to the general regulatory framework for computational modelling and simulations used in the healthcare sphere in the context of medical device development.
Table of content
The Food and Drug Administration (FDA or the Agency), the US regulating authority of healthcare products, has published a guidance document dedicated to assessing the credibility of computational modelling and simulation in medical device submissions.
The document provides an overview of the applicable regulatory requirements, as well as additional clarifications and recommendations to be taken into consideration by medical device manufacturers and other parties involved to ensure compliance thereto.
At the same time, provisions of the guidance are non-binding in their legal nature, nor are they intended to introduce new rules or impose new obligations.
Moreover, the authority explicitly states that an alternative approach could be applied, provided such an approach is in line with the existing regulatory framework and has been agreed with the authority in advance.
Terms and Definitions
First of all, the document provides definitions of the most important terms and concepts used in the context of computational modelling and simulation when applied to medical devices. This includes, inter alia, the following:
- Adequacy assessment
For a given context of use (COU), evaluating the credibility evidence in support of a computational mode, together with any other relevant information, possibly including results from the COU simulations, and deciding on whether the evidence is sufficient considering the model risk. - Calculation verification (solution verification)
The process of determining the solution accuracy of a calculation. - Code verification
The process of identifying errors in the numerical algorithms of a computer code. - Computational model
The numerical implementation of the mathematical model was performed using a computer. - Credibility
The trust, established through the collection of evidence, in the predictive capability of a computational model for a context of use. - Mathematical model
The mathematical equations, boundary conditions, initial conditions, and modelling data needed to describe a conceptual model. - Prospective adequacy assessment
Adequacy assessment performed before executing planned credibility assessment activities, using selected credibility goals and any other relevant information.
The Concept of Credibility in Computational Modeling
As further explained by the FDA, one of the most important concepts described in this guidance is the notion of credibility, defined as the established trust in a computational model’s predictive capability for a given context of use (COU).
This involves considering various elements such as the relevance and accuracy of the model, the significance of decision consequences resulting from the model’s use, and the degree of risk associated with potential inaccuracies in the model.
Structured Framework for Regulatory Submissions
The document recommends a structured framework for developing and assessing the credibility of computational models used in medical device regulatory submissions. This process begins with defining the specific questions of interest and the context in which the model will be used.
It then progresses through evaluating model risk, identifying and categorizing credibility evidence, and defining credibility factors.
The framework emphasizes the importance of both prospective and post-study adequacy assessments to determine if the model is suitable for its intended use, given the assessed risks.
Alignment with ASME V&V 40 Standards
The guidance aligns with the ASME V&V 40 standards, providing a detailed comparison between the steps of this framework and the relevant sections of ASME V&V 40.
This comparison underscores the consistency of the guidelines with established standards while also highlighting additional recommendations specific to medical device regulatory submissions.
It is important to mention that while the framework presents a systematic approach to assessing computational modelling and simulation credibility, it also allows for alternative methods.
In such cases, the document advises clearly defining the model’s context of use within the regulatory submission and providing a rationale for its credibility.
This flexibility ensures that the guidelines can accommodate a wide range of models and contexts, making it a versatile tool in the regulatory assessment of medical devices.
Conclusion
In summary, the present FDA guidance provides an overview of the existing regulatory requirements for computational modelling and simulation as set forth under the applicable legislation.
The document provides definitions of the key points and concepts and also highlights the most important aspects to be taken into consideration.
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