Audio Overview: Verification and Validation Activities for Computational Models with ASME V&V 40-2018
About This Audio Overview
In this audio overview, we delve into the transformative role of Computational Modeling and Simulation (CM&S) in medical device development and beyond, exploring how these advanced virtual tools are reshaping regulatory pathways and accelerating innovation. You'll learn how CM&S, encompassing various physics-based simulations like Finite Element Analysis (FEA) for structural mechanics and Computational Fluid Dynamics (CFD) for fluid flow, has become a pivotal tool throughout the entire product life cycle of medical devices.
We highlight the key advantages of CM&S over traditional physical testing, demonstrating how it offers:
- Cost-effectiveness: Drastically reducing the need for physical prototypes and expensive lab or animal tests, allowing developers to "fail fast" virtually.
- Time efficiency: Accelerating time-to-market by shortening design-build-test cycles, potentially shaving months off development timelines and speeding patient access to innovations.
- Safety and risk reduction: Mitigating risk to both human and animal test subjects by investigating potential failure modes and hazardous scenarios in silico, even allowing for in silico clinical trials and virtual patient modeling that can supplement or replace certain animal and human trials.
- Richness of data and insights: Yielding detailed spatial and temporal information that is often impractical or impossible to obtain physically, leading to a deeper understanding of device function and enabling comprehensive parameter sweeps for optimization.
A major focus of our overview is the FDA's progressive strategy and guidance on computational modeling. We discuss how the FDA actively promotes and recognizes CM&S evidence for device approval and clearance, aligning closely with the ASME V&V 40-2018 standard. This framework provides a structured, risk-informed credibility assessment framework, defining how simulations should be verified and validated to ensure trust in their predictive capability. This includes:
- Code Verification: Ensuring the software correctly solves the underlying equations.
- Calculation Verification: Confirming the model is solved with sufficient accuracy, accounting for potential errors in discretization, numerical solvers, and user inputs.
- Validation: Comparing model predictions to physical data, spanning bench-top experiments, in vivo animal data, clinical data, and more.
Crucially, we touch upon the groundbreaking announcement from the FDA about their plan to phase out animal testing requirements for monoclonal antibodies and other drugs. This initiative directly embraces the power of CM&S by encouraging developers to leverage AI-based computational models of toxicity and human-based lab models like organoids and organ-on-a-chip systems as more effective, human-relevant alternatives. This move is poised to reduce animal experimentation, lower R&D costs, and get safer treatments to patients faster.
The audio overview ultimately underscores that CM&S is not just a theoretical exercise but a proven, transformative approach for regulatory clearance, offering a win-win of faster innovation cycles, robust assurance of safety and efficacy, and a more humane approach to drug and device development.